thsluck commited on
Commit
3abaf6f
·
verified ·
1 Parent(s): dca3d0b

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +63 -127
README.md CHANGED
@@ -2,198 +2,134 @@
2
  library_name: transformers
3
  tags: []
4
  ---
5
-
6
- # Model Card for Model ID
7
 
8
  <!-- Provide a quick summary of what the model is/does. -->
9
 
10
 
11
 
12
  ## Model Details
 
 
13
 
14
  ### Model Description
15
 
16
  <!-- Provide a longer summary of what this model is. -->
17
 
18
- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
19
-
20
- - **Developed by:** [More Information Needed]
21
- - **Funded by [optional]:** [More Information Needed]
22
- - **Shared by [optional]:** [More Information Needed]
23
- - **Model type:** [More Information Needed]
24
- - **Language(s) (NLP):** [More Information Needed]
25
- - **License:** [More Information Needed]
26
- - **Finetuned from model [optional]:** [More Information Needed]
27
-
28
- ### Model Sources [optional]
29
-
30
- <!-- Provide the basic links for the model. -->
31
-
32
- - **Repository:** [More Information Needed]
33
- - **Paper [optional]:** [More Information Needed]
34
- - **Demo [optional]:** [More Information Needed]
35
-
36
- ## Uses
37
-
38
- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
-
40
- ### Direct Use
41
-
42
- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
-
44
- [More Information Needed]
45
-
46
- ### Downstream Use [optional]
47
-
48
- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
-
50
- [More Information Needed]
51
-
52
- ### Out-of-Scope Use
53
-
54
- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
-
56
- [More Information Needed]
57
-
58
- ## Bias, Risks, and Limitations
59
-
60
- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
-
62
- [More Information Needed]
63
-
64
- ### Recommendations
65
-
66
- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
-
68
- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
-
70
- ## How to Get Started with the Model
71
-
72
- Use the code below to get started with the model.
73
-
74
- [More Information Needed]
75
-
76
- ## Training Details
77
-
78
- ### Training Data
79
-
80
- <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
-
82
- [More Information Needed]
83
-
84
- ### Training Procedure
85
 
86
- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
 
 
 
87
 
88
- #### Preprocessing [optional]
 
 
 
89
 
90
- [More Information Needed]
91
 
 
 
92
 
93
- #### Training Hyperparameters
94
 
95
- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
 
97
- #### Speeds, Sizes, Times [optional]
98
 
99
- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
 
101
- [More Information Needed]
102
 
103
- ## Evaluation
104
 
105
- <!-- This section describes the evaluation protocols and provides the results. -->
106
 
107
- ### Testing Data, Factors & Metrics
108
 
109
- #### Testing Data
110
 
111
- <!-- This should link to a Dataset Card if possible. -->
112
 
113
- [More Information Needed]
114
 
115
- #### Factors
116
 
117
- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
 
119
- [More Information Needed]
120
 
121
- #### Metrics
122
 
123
- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
 
125
- [More Information Needed]
126
 
127
- ### Results
128
 
129
- [More Information Needed]
130
 
131
- #### Summary
132
 
 
133
 
134
 
135
- ## Model Examination [optional]
136
 
137
- <!-- Relevant interpretability work for the model goes here -->
138
 
139
- [More Information Needed]
140
 
141
- ## Environmental Impact
142
 
143
- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
 
145
- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
 
147
- - **Hardware Type:** [More Information Needed]
148
- - **Hours used:** [More Information Needed]
149
- - **Cloud Provider:** [More Information Needed]
150
- - **Compute Region:** [More Information Needed]
151
- - **Carbon Emitted:** [More Information Needed]
152
 
153
- ## Technical Specifications [optional]
154
 
155
- ### Model Architecture and Objective
156
 
157
- [More Information Needed]
158
 
159
- ### Compute Infrastructure
160
 
161
- [More Information Needed]
162
 
163
- #### Hardware
164
 
165
- [More Information Needed]
166
 
167
- #### Software
168
 
169
- [More Information Needed]
170
 
171
- ## Citation [optional]
172
 
173
- <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
 
175
- **BibTeX:**
176
 
177
- [More Information Needed]
178
 
179
- **APA:**
180
 
181
- [More Information Needed]
182
 
183
- ## Glossary [optional]
184
 
185
- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
 
187
- [More Information Needed]
188
 
189
- ## More Information [optional]
190
 
191
- [More Information Needed]
192
 
193
- ## Model Card Authors [optional]
194
 
195
- [More Information Needed]
196
 
197
- ## Model Card Contact
198
 
199
- [More Information Needed]
 
 
 
 
2
  library_name: transformers
3
  tags: []
4
  ---
5
+ # DoRA
 
6
 
7
  <!-- Provide a quick summary of what the model is/does. -->
8
 
9
 
10
 
11
  ## Model Details
12
+ This repository features a **DoRA** fine-tuned model for tweet sentiment classification trained as part of **VK**'s LLM course.
13
+
14
 
15
  ### Model Description
16
 
17
  <!-- Provide a longer summary of what this model is. -->
18
 
19
+ **PEFT** (Parameter-Efficient Fine-Tuning) and **DoRA** (Weight-Decomposed Low-Rank Adaptation) are two techniques used in machine learning to efficiently
20
+ adapt large pre-trained neural networks to specific tasks without requiring extensive computational resources.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
21
 
22
+ **PEFT** (Parameter-Efficient Fine-Tuning): **PEFT** is a technique that focuses on updating only a small subset of the model’s parameters during fine-tuning,
23
+ rather than the entire network. This approach reduces computational costs and memory usage, making it feasible to adapt large models to new tasks on devices
24
+ with limited resources. By targeting specific layers or parameters that are most relevant for the task, **PEFT** achieves significant improvements in efficiency
25
+ while maintaining performance.
26
 
27
+ **DoRA** (Weight-Decomposed Low-Rank Adaptation): **DoRA** is a technique for efficiently fine-tuning large pre-trained models by decomposing weight updates into
28
+ low-rank components. This method separates the magnitude and direction of weight updates, allowing for focused and parameter-efficient adaptations.
29
+ By targeting only the most influential components, **DoRA** reduces computational and memory demands while maintaining model performance.
30
+ This approach is particularly useful for adapting models in resource-constrained environments, enabling scalable fine-tuning with minimal resource usage.
31
 
 
32
 
33
+ In this case, **OuteAI/Lite-Oute-1-300M-Instruct** is used as the pre-trained model. This model is further fine-tuned using **DoRA** to classify tweet's sentiment.
34
+ ## Examples
35
 
36
+ ### Before fine-tuning
37
 
38
+ **Tweet:** QT @user In the original draft of the 7th book, Remus Lupin survived the Battle of Hogwarts. #HappyBirthdayRemusLupin
39
 
40
+ **True:** positive
41
 
42
+ **Predicted:** The sentiment of the text is negative.
43
 
44
+ ==================================================================================================================================================
45
 
46
+ **Tweet:** "Ben Smith / Smith (concussion) remains out of the lineup Thursday, Curtis #NHL #SJ"
47
 
48
+ **True:** neutral
49
 
50
+ **Predicted:** The sentiment of the text is negative.
51
 
52
+ ==================================================================================================================================================
53
 
54
+ **Tweet:** Sorry bout the stream last night I crashed out but will be on tonight for sure. Then back to Minecraft in pc tomorrow night.
55
 
56
+ **True:** neutral
57
 
58
+ **Predicted:** The sentiment of the text is negative.
59
 
60
+ ==================================================================================================================================================
61
 
62
+ **Tweet:** Chase Headley's RBI double in the 8th inning off David Price snapped a Yankees streak of 33 consecutive scoreless innings against Blue Jays
63
 
64
+ **True:** neutral
65
 
66
+ **Predicted:** The sentiment of the text is negative.
67
 
68
+ ==================================================================================================================================================
69
 
70
+ **Tweet:** @user Alciato: Bee will invest 150 million in January, another 200 in the Summer and plans to bring Messi by 2017"
71
 
72
+ **True:** positive
73
 
74
+ **Predicted:** The sentiment of the text is negative.
75
 
76
+ ==================================================================================================================================================
77
 
78
 
79
+ ### After fine-tuning
80
 
81
+ **Tweet:** "QT @user In the original draft of the 7th book, Remus Lupin survived the Battle of Hogwarts. #HappyBirthdayRemusLupin"
82
 
83
+ **True:** positive
84
 
85
+ **Predicted:** positive
86
 
87
+ ==================================================================================================================================================
88
 
89
+ **Tweet:** "Ben Smith / Smith (concussion) remains out of the lineup Thursday, Curtis #NHL #SJ"
90
 
91
+ **True:** neutral
 
 
 
 
92
 
93
+ **Predicted:** neutral
94
 
95
+ ==================================================================================================================================================
96
 
97
+ **Tweet:** Sorry bout the stream last night I crashed out but will be on tonight for sure. Then back to Minecraft in pc tomorrow night.
98
 
99
+ **True:** neutral
100
 
101
+ **Predicted:** neutral
102
 
103
+ ==================================================================================================================================================
104
 
105
+ **Tweet:** Chase Headley's RBI double in the 8th inning off David Price snapped a Yankees streak of 33 consecutive scoreless innings against Blue Jays
106
 
107
+ **True:** neutral
108
 
109
+ **Predicted:** neutral
110
 
111
+ ==================================================================================================================================================
112
 
113
+ **Tweet:** @user Alciato: Bee will invest 150 million in January, another 200 in the Summer and plans to bring Messi by 2017"
114
 
115
+ **True:** positive
116
 
117
+ **Predicted:** neutral
118
 
 
119
 
 
120
 
121
+ ## Analysis
122
 
123
+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/67cdb5101908dc5b357809ca/sqdkytzBV4Km_FbYEyPW0.png)
124
 
 
125
 
126
+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/67cdb5101908dc5b357809ca/xQ3s6oNU6Gn9g3j_IygNB.png)
127
 
 
128
 
 
129
 
 
130
 
 
131
 
132
+ ## References
133
+ * Model: OuteAI/Lite-Oute-1-300M-Instruct
134
+ * Dataset: cardiffnlp/tweet_eval
135
+ * Original Article: https://arxiv.org/pdf/2402.09353