Mistral-7B-Instruct-v0.2-miracl-raft-sft-v2.0
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the nthakur/miracl-raft-sft-instruct-v0.2 dataset. It achieves the following results on the evaluation set:
- Loss: 1.2086
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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 2
- total_train_batch_size: 24
- total_eval_batch_size: 12
- 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 |
|---|---|---|---|
| 1.3095 | 0.0987 | 200 | 1.2800 |
| 1.249 | 0.1975 | 400 | 1.2516 |
| 1.2514 | 0.2962 | 600 | 1.2369 |
| 1.275 | 0.3950 | 800 | 1.2263 |
| 1.1984 | 0.4937 | 1000 | 1.2197 |
| 1.1556 | 0.5924 | 1200 | 1.2149 |
| 1.2386 | 0.6912 | 1400 | 1.2116 |
| 1.2661 | 0.7899 | 1600 | 1.2096 |
| 1.2752 | 0.8887 | 1800 | 1.2088 |
| 1.2701 | 0.9874 | 2000 | 1.2086 |
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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Model tree for nthakur/Mistral-7B-Instruct-v0.2-miracl-raft-sft-v2.0
Base model
mistralai/Mistral-7B-Instruct-v0.2