File size: 2,256 Bytes
ad6d2f8 8138dbc ad6d2f8 8138dbc ad6d2f8 8138dbc ad6d2f8 8138dbc ad6d2f8 |
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 77 78 79 |
---
base_model: mistralai/Mistral-7B-Instruct-v0.3
datasets:
- GaetanMichelet/chat-60_ft_task-1_auto
library_name: peft
license: apache-2.0
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Mistral-7B_task-1_60-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-1_60-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 GaetanMichelet/chat-60_ft_task-1_auto dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8264
## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 1.7884 | 0.8696 | 5 | 1.6039 |
| 1.4942 | 1.9130 | 11 | 1.2939 |
| 1.0868 | 2.9565 | 17 | 0.9507 |
| 0.809 | 4.0 | 23 | 0.8648 |
| 0.6926 | 4.8696 | 28 | 0.8264 |
| 0.5667 | 5.9130 | 34 | 0.8804 |
| 0.3857 | 6.9565 | 40 | 0.9486 |
| 0.2768 | 8.0 | 46 | 1.1056 |
| 0.2153 | 8.8696 | 51 | 1.1607 |
| 0.1746 | 9.9130 | 57 | 1.1831 |
| 0.136 | 10.9565 | 63 | 1.1962 |
| 0.1149 | 12.0 | 69 | 1.2956 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |