mistral-sum-r16a16longer
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6498
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- training_steps: 500
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.196 | 0.0331 | 20 | 1.7916 |
1.6952 | 0.0663 | 40 | 1.7285 |
1.6458 | 0.0994 | 60 | 1.7016 |
1.6835 | 0.1326 | 80 | 1.6930 |
1.636 | 0.1657 | 100 | 1.6898 |
1.6294 | 0.1988 | 120 | 1.6890 |
1.67 | 0.2320 | 140 | 1.6813 |
1.6695 | 0.2651 | 160 | 1.6818 |
1.6442 | 0.2983 | 180 | 1.6784 |
1.6376 | 0.3314 | 200 | 1.6720 |
1.6094 | 0.3645 | 220 | 1.6692 |
1.6205 | 0.3977 | 240 | 1.6700 |
1.6372 | 0.4308 | 260 | 1.6663 |
1.6511 | 0.4640 | 280 | 1.6675 |
1.6071 | 0.4971 | 300 | 1.6705 |
1.6609 | 0.5302 | 320 | 1.6615 |
1.6039 | 0.5634 | 340 | 1.6576 |
1.6411 | 0.5965 | 360 | 1.6545 |
1.6363 | 0.6297 | 380 | 1.6551 |
1.6341 | 0.6628 | 400 | 1.6512 |
1.6123 | 0.6959 | 420 | 1.6492 |
1.6368 | 0.7291 | 440 | 1.6508 |
1.6265 | 0.7622 | 460 | 1.6513 |
1.6028 | 0.7954 | 480 | 1.6504 |
1.6229 | 0.8285 | 500 | 1.6498 |
Framework versions
- PEFT 0.11.2.dev0
- Transformers 4.42.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for Taizer/mistral-sum-r16a16longer
Base model
mistralai/Mistral-7B-v0.1