README.md

---
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-att-take-4
  results: []
---

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# libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-att-take-4

This model is a fine-tuned version of [rohitp1/libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-att-take-2](https://huggingface.co/rohitp1/libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-att-take-2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 37.5364
- Wer: 0.3334

## 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: 0.002
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 43.7806       | 0.9   | 400  | 41.3073         | 0.2570 |
| 48.6549       | 1.8   | 800  | 41.8945         | 0.2740 |
| 57.4209       | 2.7   | 1200 | 39.9947         | 0.2872 |
| 68.8449       | 3.59  | 1600 | 39.4528         | 0.3059 |
| 79.4299       | 4.49  | 2000 | 38.9575         | 0.3179 |
| 93.0514       | 5.39  | 2400 | 37.5364         | 0.3334 |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.11.0