Meta-Llama-3-8B-Instruct-miracl-raft-sft-v2.0
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the nthakur/miracl-raft-sft-instruct-v0.2 dataset. It achieves the following results on the evaluation set:
- Loss: 1.4193
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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.5961 | 0.1316 | 200 | 1.4755 |
| 1.6583 | 0.2633 | 400 | 1.4443 |
| 1.5272 | 0.3949 | 600 | 1.4324 |
| 1.5215 | 0.5266 | 800 | 1.4255 |
| 1.4857 | 0.6582 | 1000 | 1.4218 |
| 1.5324 | 0.7899 | 1200 | 1.4199 |
| 1.5235 | 0.9215 | 1400 | 1.4193 |
Framework versions
- PEFT 0.7.1
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Base model
meta-llama/Meta-Llama-3-8B-Instruct