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---
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-xls-r-300m
datasets:
- ml-superb-subset
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-ml-superb-xty
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: ml-superb-subset
type: ml-superb-subset
config: xty
split: test
args: xty
metrics:
- type: wer
value: 0.8114393463230672
name: Wer
---
<!-- 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. -->
# wav2vec2-large-xls-r-300m-ml-superb-xty
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the ml-superb-subset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6099
- Wer: 0.8114
## 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: 0.0003
- 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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 3.1825 | 0.8219 | 30 | 3.2071 | 1.0 |
| 3.0491 | 1.6438 | 60 | 3.0508 | 1.0 |
| 2.9717 | 2.4658 | 90 | 3.0385 | 1.0 |
| 2.93 | 3.2877 | 120 | 2.9222 | 1.0 |
| 2.6444 | 4.1096 | 150 | 2.3753 | 0.9931 |
| 2.05 | 4.9315 | 180 | 1.9591 | 0.9868 |
| 1.6856 | 5.7534 | 210 | 1.7810 | 0.9478 |
| 1.4182 | 6.5753 | 240 | 1.6843 | 0.8843 |
| 1.1773 | 7.3973 | 270 | 1.6370 | 0.8554 |
| 1.0521 | 8.2192 | 300 | 1.5868 | 0.8215 |
| 0.881 | 9.0411 | 330 | 1.5935 | 0.8202 |
| 0.7605 | 9.8630 | 360 | 1.6099 | 0.8114 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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