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speecht5_finetuned_fleurs_zh_4000
This model is a fine-tuned version of microsoft/speecht5_tts on the fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.3888
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: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.7366 | 1.09 | 100 | 0.6059 |
| 0.5892 | 2.19 | 200 | 0.5104 |
| 0.5436 | 3.28 | 300 | 0.4585 |
| 0.4848 | 4.38 | 400 | 0.4333 |
| 0.4733 | 5.47 | 500 | 0.4276 |
| 0.4534 | 6.57 | 600 | 0.4194 |
| 0.454 | 7.66 | 700 | 0.4172 |
| 0.4489 | 8.76 | 800 | 0.4111 |
| 0.4401 | 9.85 | 900 | 0.4108 |
| 0.441 | 10.94 | 1000 | 0.4136 |
| 0.437 | 12.04 | 1100 | 0.4078 |
| 0.4333 | 13.13 | 1200 | 0.4067 |
| 0.4328 | 14.23 | 1300 | 0.4002 |
| 0.4289 | 15.32 | 1400 | 0.4015 |
| 0.4254 | 16.42 | 1500 | 0.4012 |
| 0.427 | 17.51 | 1600 | 0.4020 |
| 0.4273 | 18.6 | 1700 | 0.4008 |
| 0.4222 | 19.7 | 1800 | 0.3966 |
| 0.4305 | 20.79 | 1900 | 0.3998 |
| 0.4198 | 21.89 | 2000 | 0.3954 |
| 0.4225 | 22.98 | 2100 | 0.3961 |
| 0.4223 | 24.08 | 2200 | 0.3965 |
| 0.4201 | 25.17 | 2300 | 0.3922 |
| 0.4234 | 26.27 | 2400 | 0.3939 |
| 0.4213 | 27.36 | 2500 | 0.3930 |
| 0.4182 | 28.45 | 2600 | 0.3934 |
| 0.4119 | 29.55 | 2700 | 0.3925 |
| 0.4113 | 30.64 | 2800 | 0.3907 |
| 0.4131 | 31.74 | 2900 | 0.3907 |
| 0.4135 | 32.83 | 3000 | 0.3933 |
| 0.4142 | 33.93 | 3100 | 0.3909 |
| 0.4144 | 35.02 | 3200 | 0.3919 |
| 0.414 | 36.11 | 3300 | 0.3919 |
| 0.418 | 37.21 | 3400 | 0.3899 |
| 0.4094 | 38.3 | 3500 | 0.3897 |
| 0.4149 | 39.4 | 3600 | 0.3924 |
| 0.4105 | 40.49 | 3700 | 0.3905 |
| 0.413 | 41.59 | 3800 | 0.3895 |
| 0.4117 | 42.68 | 3900 | 0.3900 |
| 0.4096 | 43.78 | 4000 | 0.3888 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
