toolalpaca
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the toolalpaca dataset. It achieves the following results on the evaluation set:
- Loss: 0.2505
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2781 | 0.7407 | 500 | 0.2681 |
| 0.1417 | 1.4815 | 1000 | 0.2399 |
| 0.0362 | 2.2222 | 1500 | 0.2555 |
| 0.0244 | 2.9630 | 2000 | 0.2507 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Inference Providers
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Model tree for shipWr3ck/toolalpaca-llama3.1-8b-Instruct
Base model
meta-llama/Llama-3.1-8B
Finetuned
meta-llama/Llama-3.1-8B-Instruct