File size: 2,236 Bytes
b532629 137a6c9 b532629 547e632 b532629 547e632 b532629 496154b b532629 137a6c9 b532629 496154b b532629 137a6c9 496154b b532629 dac3171 b532629 |
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 |
---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mt5-small-task1-dataset2
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. -->
# mt5-small-task1-dataset2
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0670
- Accuracy: 0.19
## 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: 5.6e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 10.1157 | 1.0 | 250 | 2.0629 | 0.0 |
| 2.7164 | 2.0 | 500 | 1.6984 | 0.092 |
| 2.1384 | 3.0 | 750 | 1.6345 | 0.098 |
| 1.8496 | 4.0 | 1000 | 1.5214 | 0.118 |
| 1.6276 | 5.0 | 1250 | 1.3418 | 0.14 |
| 1.469 | 6.0 | 1500 | 1.2577 | 0.15 |
| 1.3461 | 7.0 | 1750 | 1.2325 | 0.162 |
| 1.2791 | 8.0 | 2000 | 1.1790 | 0.16 |
| 1.2349 | 9.0 | 2250 | 1.1320 | 0.174 |
| 1.1826 | 10.0 | 2500 | 1.1118 | 0.176 |
| 1.1504 | 11.0 | 2750 | 1.1063 | 0.19 |
| 1.1327 | 12.0 | 3000 | 1.0731 | 0.186 |
| 1.1168 | 13.0 | 3250 | 1.0617 | 0.186 |
| 1.1038 | 14.0 | 3500 | 1.0735 | 0.182 |
| 1.0929 | 15.0 | 3750 | 1.0670 | 0.19 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
|