llama-3.2-1b-finetuned-corpus
This model is a fine-tuned version of unsloth/Llama-3.2-1B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8084
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: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 256
- total_eval_batch_size: 32
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.0687 | 0.0700 | 200 | 2.0610 |
| 1.9664 | 0.1400 | 400 | 1.9985 |
| 1.9066 | 0.2101 | 600 | 1.9431 |
| 1.8604 | 0.2801 | 800 | 1.9049 |
| 1.8181 | 0.3501 | 1000 | 1.8786 |
| 1.813 | 0.4201 | 1200 | 1.8582 |
| 1.8095 | 0.4902 | 1400 | 1.8415 |
| 1.7891 | 0.5602 | 1600 | 1.8284 |
| 1.7767 | 0.6302 | 1800 | 1.8188 |
| 1.7777 | 0.7002 | 2000 | 1.8130 |
| 1.7725 | 0.7703 | 2200 | 1.8099 |
| 1.768 | 0.8403 | 2400 | 1.8087 |
| 1.7633 | 0.9103 | 2600 | 1.8084 |
| 1.7646 | 0.9803 | 2800 | 1.8084 |
Framework versions
- Transformers 4.50.0
- Pytorch 2.5.1+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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