File size: 1,874 Bytes
5204d25 41b3057 5204d25 41b3057 5204d25 d6a5a49 5204d25 ae106cc 5204d25 41b3057 5204d25 41b3057 5204d25 41b3057 5204d25 41b3057 5204d25 41b3057 5204d25 41b3057 |
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 |
---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
datasets:
- scitldr
base_model: mistralai/Mistral-7B-Instruct-v0.2
model-index:
- name: Mistral-Summarization
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 Summarization
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the scitldr dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1059
## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.0732 | 0.1 | 200 | 2.1863 |
| 2.1324 | 0.2 | 400 | 2.1925 |
| 2.103 | 0.3 | 600 | 2.1876 |
| 2.0766 | 0.4 | 800 | 2.1737 |
| 2.0825 | 0.5 | 1000 | 2.1555 |
| 2.0731 | 0.6 | 1200 | 2.1465 |
| 2.0819 | 0.7 | 1400 | 2.1355 |
| 1.9802 | 0.8 | 1600 | 2.1223 |
| 2.0466 | 0.9 | 1800 | 2.1059 |
### Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2 |