cls_sentiment_mistral_v1
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 0.5972
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: 0.0002
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.7365 | 0.1986 | 50 | 0.7344 |
0.6778 | 0.3972 | 100 | 0.6852 |
0.6548 | 0.5958 | 150 | 0.6588 |
0.6728 | 0.7944 | 200 | 0.6333 |
0.6148 | 0.9930 | 250 | 0.6106 |
0.43 | 1.1917 | 300 | 0.6174 |
0.4575 | 1.3903 | 350 | 0.6081 |
0.4225 | 1.5889 | 400 | 0.6058 |
0.4136 | 1.7875 | 450 | 0.5976 |
0.441 | 1.9861 | 500 | 0.5972 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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mistralai/Mistral-7B-Instruct-v0.2
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