90d0bc3c-644e-4b06-8933-8c73b805805c
This model is a fine-tuned version of bigscience/bloomz-560m on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.7240
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: 0.000214
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 500
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.0008 | 1 | 4.9157 |
| 7.3861 | 0.0408 | 50 | 3.8693 |
| 6.837 | 0.0816 | 100 | 3.4392 |
| 6.3293 | 0.1224 | 150 | 3.2294 |
| 5.9831 | 0.1632 | 200 | 3.0641 |
| 6.0264 | 0.2040 | 250 | 2.9398 |
| 5.6246 | 0.2448 | 300 | 2.8624 |
| 5.6646 | 0.2856 | 350 | 2.7947 |
| 5.352 | 0.3264 | 400 | 2.7493 |
| 5.6181 | 0.3672 | 450 | 2.7282 |
| 5.5604 | 0.4080 | 500 | 2.7240 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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Base model
bigscience/bloomz-560m