BitLlama2-jp-127M-optim-1
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.3189
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: 0.0024
- train_batch_size: 96
- eval_batch_size: 96
- seed: 42
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
6.8029 | 0.07 | 200 | 4.8467 |
4.5453 | 0.14 | 400 | 4.3280 |
4.2342 | 0.22 | 600 | 4.0933 |
4.0181 | 0.29 | 800 | 3.9435 |
3.881 | 0.36 | 1000 | 3.8287 |
3.7829 | 0.43 | 1200 | 3.7290 |
3.6972 | 0.51 | 1400 | 3.6557 |
3.63 | 0.58 | 1600 | 3.5933 |
3.5578 | 0.65 | 1800 | 3.5317 |
3.5077 | 0.72 | 2000 | 3.4725 |
3.4441 | 0.8 | 2200 | 3.4209 |
3.3902 | 0.87 | 2400 | 3.3638 |
3.3464 | 0.94 | 2600 | 3.3189 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Downloads last month
- 10
Inference API (serverless) does not yet support model repos that contain custom code.