---
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
datasets:
- ml-superb-subset
metrics:
- wer
model-index:
- name: w2v-bert-2.0-ml-superb-xty
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: ml-superb-subset
      type: ml-superb-subset
      config: xty
      split: test
      args: xty
    metrics:
    - name: Wer
      type: wer
      value: 1.3984915147705845
---

<!-- 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. -->

# w2v-bert-2.0-ml-superb-xty

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the ml-superb-subset dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3981
- Wer: 1.3985

## 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: 30
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 3.5467        | 0.8219 | 30   | 2.8636          | 1.0    |
| 2.4639        | 1.6438 | 60   | 2.5298          | 1.0094 |
| 2.38          | 2.4658 | 90   | 2.4983          | 1.1263 |
| 2.2725        | 3.2877 | 120  | 2.4866          | 1.2319 |
| 2.2608        | 4.1096 | 150  | 2.5116          | 1.5405 |
| 2.2222        | 4.9315 | 180  | 2.4588          | 1.3300 |
| 2.2609        | 5.7534 | 210  | 2.4448          | 1.3451 |
| 2.1665        | 6.5753 | 240  | 2.4270          | 1.3199 |
| 2.1703        | 7.3973 | 270  | 2.4223          | 1.3576 |
| 2.1366        | 8.2192 | 300  | 2.4054          | 1.4085 |
| 2.123         | 9.0411 | 330  | 2.4006          | 1.4180 |
| 2.1331        | 9.8630 | 360  | 2.3981          | 1.3985 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1