transformers safetensors wav2vec2 automatic-speech-recognition generated_from_trainer base_model:facebook/wav2vec2-xls-r-300m license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: XLS-R_Synthesis_GN_v1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# XLS-R_Synthesis_GN_v1

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5071
- Wer: 0.3125

## 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: 18
- eval_batch_size: 9
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 72
- total_eval_batch_size: 18
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 5.5691        | 1.0   | 1252  | 2.9844          | 1.0    |
| 1.7927        | 2.0   | 2505  | 0.5051          | 0.5816 |
| 0.5062        | 3.0   | 3757  | 0.3025          | 0.3928 |
| 0.3566        | 4.0   | 5010  | 0.2515          | 0.3208 |
| 0.2883        | 5.0   | 6262  | 0.2237          | 0.2811 |
| 0.2474        | 6.0   | 7515  | 0.2055          | 0.2538 |
| 0.223         | 7.0   | 8767  | 0.1929          | 0.2394 |
| 0.2068        | 8.0   | 10020 | 0.1957          | 0.2354 |
| 0.2043        | 9.0   | 11272 | 0.2222          | 0.2486 |
| 0.3093        | 10.0  | 12525 | 0.3168          | 0.3350 |
| 0.2501        | 11.0  | 13777 | 0.2099          | 0.2458 |
| 0.3961        | 12.0  | 15030 | 0.5071          | 0.3125 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
