emotion-classifier

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,69 @@
+---
+library_name: transformers
+license: mit
+base_model: abdeljalilELmajjodi/model
+tags:
+- generated_from_trainer
+metrics:
+- f1
+model-index:
+- name: emotion_classifier
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# emotion_classifier
+
+This model is a fine-tuned version of [abdeljalilELmajjodi/model](https://huggingface.co/abdeljalilELmajjodi/model) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.7268
+- F1: {'f1': 0.4749679405113014}
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 4
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.03
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | F1                          |
+|:-------------:|:------:|:----:|:---------------:|:---------------------------:|
+| 6.8728        | 0.9950 | 100  | 1.8998          | {'f1': 0.3554471709728371}  |
+| 6.545         | 1.9851 | 200  | 1.7557          | {'f1': 0.4311025882104702}  |
+| 5.7745        | 2.9751 | 300  | 1.7189          | {'f1': 0.45241170661760866} |
+| 5.1439        | 3.9652 | 400  | 1.7268          | {'f1': 0.4629496833729773}  |
+| 4.6931        | 4.9552 | 500  | 1.7268          | {'f1': 0.4749679405113014}  |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

config.json

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+    "XLMRobertaForSequenceClassification"
+  ],
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+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
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+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
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+  "transformers_version": "4.47.1",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

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tokenizer_config.json

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