---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_en64_lr301
  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_finetuned_en64_lr301

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4580

## 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: 32
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss |
|:-------------:|:--------:|:----:|:---------------:|
| 0.4634        | 55.1724  | 100  | 0.3961          |
| 0.3883        | 110.3448 | 200  | 0.3942          |
| 0.3614        | 165.5172 | 300  | 0.4229          |
| 0.3456        | 220.6897 | 400  | 0.4271          |
| 0.3355        | 275.8621 | 500  | 0.4273          |
| 0.3257        | 331.0345 | 600  | 0.4478          |
| 0.3194        | 386.2069 | 700  | 0.4437          |
| 0.3116        | 441.3793 | 800  | 0.4586          |
| 0.3053        | 496.5517 | 900  | 0.4518          |
| 0.2994        | 551.7241 | 1000 | 0.4535          |
| 0.2969        | 606.8966 | 1100 | 0.4594          |
| 0.2946        | 662.0690 | 1200 | 0.4521          |
| 0.2904        | 717.2414 | 1300 | 0.4569          |
| 0.2889        | 772.4138 | 1400 | 0.4573          |
| 0.2911        | 827.5862 | 1500 | 0.4580          |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1