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---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: HopefulASR
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. -->
# HopefulASR
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4022
## 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: 0.0001
- 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: 100
- training_steps: 2000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.4624 | 3.0769 | 100 | 0.4358 |
| 0.4523 | 6.1538 | 200 | 0.4288 |
| 0.4385 | 9.2308 | 300 | 0.4148 |
| 0.4288 | 12.3077 | 400 | 0.4126 |
| 0.4262 | 15.3846 | 500 | 0.4114 |
| 0.4236 | 18.4615 | 600 | 0.4128 |
| 0.416 | 21.5385 | 700 | 0.4105 |
| 0.4118 | 24.6154 | 800 | 0.4111 |
| 0.4091 | 27.6923 | 900 | 0.4074 |
| 0.4044 | 30.7692 | 1000 | 0.4085 |
| 0.4048 | 33.8462 | 1100 | 0.4080 |
| 0.402 | 36.9231 | 1200 | 0.4021 |
| 0.3957 | 40.0 | 1300 | 0.4034 |
| 0.3977 | 43.0769 | 1400 | 0.4027 |
| 0.3982 | 46.1538 | 1500 | 0.4041 |
| 0.395 | 49.2308 | 1600 | 0.4003 |
| 0.3913 | 52.3077 | 1700 | 0.4017 |
| 0.3969 | 55.3846 | 1800 | 0.4032 |
| 0.3918 | 58.4615 | 1900 | 0.4024 |
| 0.3898 | 61.5385 | 2000 | 0.4022 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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