File size: 1,716 Bytes
9ed8023
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ec2c920
 
9ed8023
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ec2c920
9ed8023
 
 
ec2c920
 
 
 
 
 
9ed8023
 
 
 
ec2c920
9ed8023
 
ec2c920
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
---
language:
- eg
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Small Eg - Tariq Hasaballah 100330
  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. -->

# Whisper Small Eg - Tariq Hasaballah 100330

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the ASR-EGARBCSC: AN EGYPTIAN ARABIC CONVERSATIONAL SPEECH CORPUS dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5626
- Wer: 47.4960

## 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: 1e-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: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.7309        | 0.7267 | 125  | 0.5984          | 52.4512 |
| 0.3608        | 1.4535 | 250  | 0.5488          | 48.6031 |
| 0.1789        | 2.1802 | 375  | 0.5537          | 46.5999 |
| 0.1844        | 2.9070 | 500  | 0.5626          | 47.4960 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1