File size: 1,730 Bytes
5188b2e
 
 
 
 
 
 
 
c3616b3
7ce7fed
5188b2e
c3616b3
5188b2e
 
 
 
 
 
c3616b3
5188b2e
c3616b3
5188b2e
c3616b3
5188b2e
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c3616b3
5188b2e
 
 
 
 
 
c3616b3
 
 
 
5188b2e
 
 
 
 
 
 
 
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
---
language:
- en
license: mit
tags:
- text-to-speech
- generated_from_trainer
datasets:
- lj_speech
base_model: Avitas8485/speecht5_tts_commonvoice_en_03
model-index:
- name: speecht5_tts_commonvoice_en_04
  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. -->

# speecht5_tts_commonvoice_en_04

This model is a fine-tuned version of [Avitas8485/speecht5_tts_commonvoice_en_03](https://huggingface.co/Avitas8485/speecht5_tts_commonvoice_en_03) on the ljspeech dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3719

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.4105        | 1.36  | 1000 | 0.3789          |
| 0.409         | 2.71  | 2000 | 0.3753          |
| 0.4076        | 4.07  | 3000 | 0.3735          |
| 0.4055        | 5.43  | 4000 | 0.3719          |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3