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---
base_model: mistralai/Mistral-7B-Instruct-v0.3
datasets:
- GaetanMichelet/chat-60_ft_task-1
- GaetanMichelet/chat-120_ft_task-1
library_name: peft
license: apache-2.0
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Mistral-7B_task-1_120-samples_config-2_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-1_120-samples_config-2_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-1 and the GaetanMichelet/chat-120_ft_task-1 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.9301
## 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: 16
- total_train_batch_size: 16
- 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 2.0764 | 0.9091 | 5 | 1.9517 |
| 1.7328 | 2.0 | 11 | 1.5258 |
| 1.2472 | 2.9091 | 16 | 1.1678 |
| 0.979 | 4.0 | 22 | 0.9953 |
| 0.909 | 4.9091 | 27 | 0.9437 |
| 0.7945 | 6.0 | 33 | 0.9338 |
| 0.6672 | 6.9091 | 38 | 0.9301 |
| 0.5517 | 8.0 | 44 | 0.9630 |
| 0.411 | 8.9091 | 49 | 1.0645 |
| 0.296 | 10.0 | 55 | 1.1561 |
| 0.2302 | 10.9091 | 60 | 1.3206 |
| 0.1752 | 12.0 | 66 | 1.3892 |
| 0.1498 | 12.9091 | 71 | 1.3749 |
| 0.1138 | 14.0 | 77 | 1.4865 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |