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---
library_name: transformers
language:
- en
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- arielcerdap/TimeStamped
metrics:
- wer
model-index:
- name: Wav2Vec2 TimeStamped Stutter - Ariel Cerda
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: TimeStamped
type: arielcerdap/TimeStamped
args: 'config: en, split: test'
metrics:
- name: Wer
type: wer
value: 0.9991797676008203
---
<!-- 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 TimeStamped Stutter - Ariel Cerda
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the TimeStamped dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Wer: 0.9992
## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 11.5515 | 1.1696 | 100 | 11.9112 | 1.0001 |
| 13.4395 | 2.3392 | 200 | 11.9112 | 1.0001 |
| 11.9169 | 3.5088 | 300 | 11.9112 | 1.0001 |
| 11.1801 | 4.6784 | 400 | 11.9112 | 1.0001 |
| 15.3393 | 5.8480 | 500 | 11.9112 | 1.0001 |
| 11.8177 | 7.0175 | 600 | 11.9112 | 1.0001 |
| 10.7941 | 8.1871 | 700 | 11.9112 | 1.0001 |
| 13.8075 | 9.3567 | 800 | 11.9112 | 1.0001 |
| 11.5275 | 10.5263 | 900 | 11.9112 | 1.0001 |
| 10.1228 | 11.6959 | 1000 | 11.9112 | 1.0001 |
| 13.7071 | 12.8655 | 1100 | 11.9112 | 1.0001 |
| 11.6933 | 14.0351 | 1200 | 11.9112 | 1.0001 |
| 10.885 | 15.2047 | 1300 | 11.9112 | 1.0001 |
| 14.2349 | 16.3743 | 1400 | 11.9112 | 1.0001 |
| 12.8886 | 17.5439 | 1500 | 11.9112 | 1.0001 |
| 0.0 | 18.7135 | 1600 | nan | 0.9992 |
| 0.0 | 19.8830 | 1700 | nan | 0.9992 |
| 0.0 | 21.0526 | 1800 | nan | 0.9992 |
| 0.0 | 22.2222 | 1900 | nan | 0.9992 |
| 0.0 | 23.3918 | 2000 | nan | 0.9992 |
| 0.0 | 24.5614 | 2100 | nan | 0.9992 |
| 0.0 | 25.7310 | 2200 | nan | 0.9992 |
| 0.0 | 26.9006 | 2300 | nan | 0.9992 |
| 0.0 | 28.0702 | 2400 | nan | 0.9992 |
| 0.0 | 29.2398 | 2500 | nan | 0.9992 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
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