llama-lima
This model is a fine-tuned version of huggyllama/llama-7b on the GAIR/lima dataset. It achieves the following results on the evaluation set:
- Loss: 1.9975
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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 16
- total_train_batch_size: 128
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.8892 | 1.0 | 6 | 1.7981 |
| 1.7346 | 2.0 | 12 | 1.7421 |
| 1.5782 | 3.0 | 18 | 1.6837 |
| 1.3988 | 4.0 | 24 | 1.7017 |
| 1.0825 | 5.0 | 30 | 1.7303 |
| 0.9252 | 6.0 | 36 | 1.8102 |
| 0.794 | 7.0 | 42 | 1.9195 |
| 0.7094 | 8.0 | 48 | 1.9669 |
| 0.6205 | 9.0 | 54 | 1.9970 |
| 0.5749 | 10.0 | 60 | 1.9975 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2
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Base model
huggyllama/llama-7b