File size: 2,240 Bytes
0d76e32
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Wav2Vec2ForSequenceClassification-finetuned-eos_poc5_ge-di-v7-meeting-v2
  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. -->

# Wav2Vec2ForSequenceClassification-finetuned-eos_poc5_ge-di-v7-meeting-v2

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6822
- Accuracy: 0.6114

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.5858        | 0.9748 | 29   | 0.6455          | 0.6517   |
| 2.5709        | 1.9748 | 58   | 0.6422          | 0.6517   |
| 2.5285        | 2.9748 | 87   | 0.6421          | 0.6517   |
| 2.4906        | 3.9748 | 116  | 0.6335          | 0.6540   |
| 2.437         | 4.9748 | 145  | 0.6330          | 0.6517   |
| 2.3735        | 5.9748 | 174  | 0.6458          | 0.5972   |
| 2.1678        | 6.9748 | 203  | 0.6553          | 0.6114   |
| 2.1317        | 7.9748 | 232  | 0.6734          | 0.5900   |
| 2.0619        | 8.9748 | 261  | 0.6809          | 0.5806   |
| 1.9324        | 9.9748 | 290  | 0.6822          | 0.6114   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0