File size: 2,126 Bytes
0e4e6d3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 |
---
base_model: mistralai/Mistral-7B-Instruct-v0.3
library_name: peft
license: apache-2.0
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Mistral-7B_task-2_180-samples_config-1_full_auto
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Mistral-7B_task-2_180-samples_config-1_full_auto
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co./mistralai/Mistral-7B-Instruct-v0.3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0511
## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_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: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0296 | 1.0 | 17 | 1.0086 |
| 0.8629 | 2.0 | 34 | 0.8535 |
| 0.7661 | 3.0 | 51 | 0.7903 |
| 0.693 | 4.0 | 68 | 0.7717 |
| 0.6638 | 5.0 | 85 | 0.7682 |
| 0.5866 | 6.0 | 102 | 0.7787 |
| 0.5466 | 7.0 | 119 | 0.8051 |
| 0.4416 | 8.0 | 136 | 0.8421 |
| 0.3585 | 9.0 | 153 | 0.8836 |
| 0.3201 | 10.0 | 170 | 0.9439 |
| 0.2796 | 11.0 | 187 | 0.9902 |
| 0.1842 | 12.0 | 204 | 1.0511 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |