File size: 2,220 Bytes
b4a3748 63a68e7 b4a3748 e94a6be b4a3748 e94a6be b4a3748 63a68e7 b4a3748 f661e6f b4a3748 63a68e7 e94a6be b4a3748 f661e6f b4a3748 |
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 |
---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mt5-small-task2-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-task2-dataset2
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4320
- Accuracy: 0.37
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 7.018 | 1.0 | 250 | 1.2234 | 0.014 |
| 1.6684 | 2.0 | 500 | 0.8157 | 0.124 |
| 1.0289 | 3.0 | 750 | 0.6527 | 0.222 |
| 0.8021 | 4.0 | 1000 | 0.5877 | 0.282 |
| 0.6964 | 5.0 | 1250 | 0.5360 | 0.3 |
| 0.6252 | 6.0 | 1500 | 0.5118 | 0.32 |
| 0.5828 | 7.0 | 1750 | 0.4899 | 0.318 |
| 0.5436 | 8.0 | 2000 | 0.4718 | 0.35 |
| 0.5232 | 9.0 | 2250 | 0.4625 | 0.34 |
| 0.5005 | 10.0 | 2500 | 0.4556 | 0.342 |
| 0.4789 | 11.0 | 2750 | 0.4436 | 0.356 |
| 0.4733 | 12.0 | 3000 | 0.4379 | 0.356 |
| 0.4651 | 13.0 | 3250 | 0.4347 | 0.366 |
| 0.4591 | 14.0 | 3500 | 0.4320 | 0.37 |
| 0.4508 | 15.0 | 3750 | 0.4320 | 0.37 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.0
|