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---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- ml-superb-subset
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-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: 1.0
---
<!-- 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: 3.2130
- Wer: 1.0
## 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: 3e-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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:---:|
| 8.25 | 0.8219 | 30 | 6.0908 | 1.0 |
| 4.6254 | 1.6438 | 60 | 4.0849 | 1.0 |
| 3.87 | 2.4658 | 90 | 3.7436 | 1.0 |
| 3.6415 | 3.2877 | 120 | 3.5797 | 1.0 |
| 3.502 | 4.1096 | 150 | 3.4716 | 1.0 |
| 3.3476 | 4.9315 | 180 | 3.3731 | 1.0 |
| 3.2852 | 5.7534 | 210 | 3.3274 | 1.0 |
| 3.2806 | 6.5753 | 240 | 3.2766 | 1.0 |
| 3.1827 | 7.3973 | 270 | 3.2398 | 1.0 |
| 3.1649 | 8.2192 | 300 | 3.2373 | 1.0 |
| 3.1544 | 9.0411 | 330 | 3.2119 | 1.0 |
| 3.1401 | 9.8630 | 360 | 3.2130 | 1.0 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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