File size: 1,498 Bytes
2a6b67c
94e34cf
 
2a6b67c
94e34cf
 
 
 
 
 
2a6b67c
 
94e34cf
 
2a6b67c
94e34cf
2a6b67c
94e34cf
 
 
 
2a6b67c
94e34cf
2a6b67c
94e34cf
2a6b67c
94e34cf
2a6b67c
94e34cf
2a6b67c
94e34cf
2a6b67c
94e34cf
2a6b67c
94e34cf
2a6b67c
94e34cf
2a6b67c
94e34cf
 
 
 
 
 
 
 
2a6b67c
94e34cf
2a6b67c
94e34cf
 
 
 
 
2a6b67c
94e34cf
 
 
 
 
 
 
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
---
license: apache-2.0
base_model: t5-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: t5-large-bn-adapter-6.34M-snli-model2
  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. -->

# t5-large-bn-adapter-6.34M-snli-model2

This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6035
- Accuracy: 0.8075

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 59
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.308         | 1.0   | 17168 | 0.2400          | 0.9135   |
| 0.288         | 2.0   | 34336 | 0.2309          | 0.9187   |
| 0.2705        | 3.0   | 51504 | 0.2298          | 0.9216   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0