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---
base_model: mistralai/Mistral-7B-Instruct-v0.3
datasets:
- GaetanMichelet/chat-60_ft_task-3
- GaetanMichelet/chat-120_ft_task-3
- GaetanMichelet/chat-180_ft_task-3
library_name: peft
license: apache-2.0
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Mistral-7B_task-3_180-samples_config-1_full
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-3_180-samples_config-1_full
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 GaetanMichelet/chat-60_ft_task-3, the GaetanMichelet/chat-120_ft_task-3 and the GaetanMichelet/chat-180_ft_task-3 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.8618
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.15 | 1.0 | 17 | 1.1231 |
| 0.9609 | 2.0 | 34 | 0.9487 |
| 0.8559 | 3.0 | 51 | 0.8850 |
| 0.7818 | 4.0 | 68 | 0.8655 |
| 0.7523 | 5.0 | 85 | 0.8618 |
| 0.6583 | 6.0 | 102 | 0.8816 |
| 0.6114 | 7.0 | 119 | 0.9062 |
| 0.4904 | 8.0 | 136 | 0.9385 |
| 0.396 | 9.0 | 153 | 1.0029 |
| 0.3441 | 10.0 | 170 | 1.0624 |
| 0.3021 | 11.0 | 187 | 1.1177 |
| 0.1931 | 12.0 | 204 | 1.1625 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |