File size: 2,133 Bytes
3660329 |
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 |
---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.2
model-index:
- name: ZeroShot-3.3.3-Mistral-7b-Multilanguage-1-epoch-3.2.0
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. -->
# ZeroShot-3.3.3-Mistral-7b-Multilanguage-1-epoch-3.2.0
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4078
## 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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 201
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.5561 | 0.1 | 20 | 0.8398 |
| 0.594 | 0.2 | 40 | 0.5099 |
| 0.4849 | 0.3 | 60 | 0.4661 |
| 0.4516 | 0.4 | 80 | 0.4328 |
| 0.4237 | 0.5 | 100 | 0.4192 |
| 0.4235 | 0.59 | 120 | 0.4142 |
| 0.4128 | 0.69 | 140 | 0.4110 |
| 0.4152 | 0.79 | 160 | 0.4090 |
| 0.4092 | 0.89 | 180 | 0.4080 |
| 0.41 | 0.99 | 200 | 0.4078 |
### Framework versions
- PEFT 0.8.2
- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.17.1
- Tokenizers 0.15.1 |