t1_5k_v9_tag5
This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on the t1_5k_v9_tag5 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3453
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: 5e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 4
- total_eval_batch_size: 4
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.3206 | 0.3922 | 100 | 0.3850 |
| 0.2667 | 0.7843 | 200 | 0.3527 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.6.0+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for lemonhat/Llama-3.1-8B-Instruct-t1_5k_v9_tag5
Base model
meta-llama/Llama-3.1-8B
Finetuned
meta-llama/Llama-3.1-8B-Instruct