sft-llama3-8b-itt
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the HuggingFaceH4/ultrachat_200k dataset. It achieves the following results on the evaluation set:
- Loss: 1.0620
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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0719 | 0.9995 | 935 | 1.0777 |
| 0.883 | 1.9989 | 1870 | 1.0620 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.19.1
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Base model
meta-llama/Meta-Llama-3-8B