File size: 2,351 Bytes
5c52761 |
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 |
---
license: llama2
base_model: bofenghuang/vigogne-2-70b-chat
tags:
- generated_from_trainer
model-index:
- name: PointCon-vigogne-2-70b-chat-3
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. -->
# PointCon-vigogne-2-70b-chat-3
This model is a fine-tuned version of [bofenghuang/vigogne-2-70b-chat](https://huggingface.co/bofenghuang/vigogne-2-70b-chat) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5719
## 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: 5e-05
- 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
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8556 | 0.05 | 30 | 1.7646 |
| 1.6805 | 0.1 | 60 | 1.6982 |
| 1.646 | 0.15 | 90 | 1.6679 |
| 1.5978 | 0.19 | 120 | 1.6567 |
| 1.6003 | 0.24 | 150 | 1.6437 |
| 1.5975 | 0.29 | 180 | 1.6339 |
| 1.5917 | 0.34 | 210 | 1.6264 |
| 1.5579 | 0.39 | 240 | 1.6111 |
| 1.5888 | 0.44 | 270 | 1.6022 |
| 1.5763 | 0.49 | 300 | 1.5966 |
| 1.5102 | 0.54 | 330 | 1.5938 |
| 1.5611 | 0.58 | 360 | 1.5877 |
| 1.6063 | 0.63 | 390 | 1.5869 |
| 1.5641 | 0.68 | 420 | 1.5870 |
| 1.5615 | 0.73 | 450 | 1.5808 |
| 1.4644 | 0.78 | 480 | 1.5761 |
| 1.4924 | 0.83 | 510 | 1.5750 |
| 1.5644 | 0.88 | 540 | 1.5735 |
| 1.5498 | 0.93 | 570 | 1.5726 |
| 1.5179 | 0.97 | 600 | 1.5719 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|