File size: 2,582 Bytes
e932913 dcfd813 e932913 dcfd813 e932913 dcfd813 e932913 dcfd813 e932913 dcfd813 e932913 dcfd813 e932913 |
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-task3-dataset3
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-task3-dataset3
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: 1.4093
- Accuracy: 0.128
- Mse: 1.5841
- Log-distance: 0.6809
- S Score: 0.4800
## 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: 12
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Mse | Log-distance | S Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------------:|:-------:|
| 2.1991 | 1.0 | 250 | 1.5275 | 0.106 | 1.7120 | 0.7824 | 0.4048 |
| 2.1115 | 2.0 | 500 | 1.5009 | 0.106 | 1.7469 | 0.8062 | 0.3844 |
| 1.8295 | 3.0 | 750 | 1.4483 | 0.108 | 1.7239 | 0.7902 | 0.3972 |
| 1.7033 | 4.0 | 1000 | 1.4335 | 0.112 | 1.7052 | 0.7759 | 0.4088 |
| 1.6426 | 5.0 | 1250 | 1.4224 | 0.12 | 1.5337 | 0.6427 | 0.5112 |
| 1.5923 | 6.0 | 1500 | 1.4236 | 0.126 | 1.6061 | 0.7015 | 0.4628 |
| 1.5529 | 7.0 | 1750 | 1.4284 | 0.122 | 1.5984 | 0.6967 | 0.4676 |
| 1.546 | 8.0 | 2000 | 1.4132 | 0.124 | 1.6032 | 0.6948 | 0.4704 |
| 1.5364 | 9.0 | 2250 | 1.4306 | 0.116 | 1.6403 | 0.7282 | 0.4460 |
| 1.5365 | 10.0 | 2500 | 1.4107 | 0.118 | 1.5702 | 0.6681 | 0.4948 |
| 1.5145 | 11.0 | 2750 | 1.4182 | 0.118 | 1.6041 | 0.7063 | 0.4596 |
| 1.5103 | 12.0 | 3000 | 1.4093 | 0.128 | 1.5841 | 0.6809 | 0.4800 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
|