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---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: Model_G_2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice
type: common_voice
config: id
split: test
args: id
metrics:
- name: Wer
type: wer
value: 0.9852694387469699
---
<!-- 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. -->
# Model_G_2
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0359
- Wer: 0.9853
- Cer: 0.7143
## 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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 3.8996 | 0.81 | 400 | 0.7268 | 1.0008 | 0.7672 |
| 0.5216 | 1.61 | 800 | 0.2765 | 1.0171 | 0.7602 |
| 0.3112 | 2.42 | 1200 | 0.1712 | 0.9965 | 0.7335 |
| 0.2343 | 3.23 | 1600 | 0.1169 | 0.9984 | 0.7262 |
| 0.1911 | 4.03 | 2000 | 0.0970 | 0.9970 | 0.7447 |
| 0.1625 | 4.84 | 2400 | 0.0834 | 0.9941 | 0.7245 |
| 0.1471 | 5.65 | 2800 | 0.0771 | 0.9936 | 0.7239 |
| 0.1301 | 6.45 | 3200 | 0.0645 | 0.9940 | 0.7330 |
| 0.1241 | 7.26 | 3600 | 0.0621 | 0.9912 | 0.7208 |
| 0.1128 | 8.06 | 4000 | 0.0672 | 0.9892 | 0.7188 |
| 0.1035 | 8.87 | 4400 | 0.0531 | 0.9895 | 0.7332 |
| 0.0993 | 9.68 | 4800 | 0.0541 | 0.9912 | 0.7374 |
| 0.0917 | 10.48 | 5200 | 0.0516 | 0.9883 | 0.7276 |
| 0.0879 | 11.29 | 5600 | 0.0507 | 0.9841 | 0.7246 |
| 0.0836 | 12.1 | 6000 | 0.0490 | 0.9858 | 0.7335 |
| 0.0767 | 12.9 | 6400 | 0.0464 | 0.9844 | 0.7231 |
| 0.0744 | 13.71 | 6800 | 0.0458 | 0.9855 | 0.7170 |
| 0.0695 | 14.52 | 7200 | 0.0506 | 0.9893 | 0.7145 |
| 0.0676 | 15.32 | 7600 | 0.0443 | 0.9892 | 0.7151 |
| 0.0621 | 16.13 | 8000 | 0.0457 | 0.9831 | 0.7188 |
| 0.0593 | 16.94 | 8400 | 0.0437 | 0.9905 | 0.7251 |
| 0.0558 | 17.74 | 8800 | 0.0419 | 0.9881 | 0.7160 |
| 0.0539 | 18.55 | 9200 | 0.0403 | 0.9897 | 0.7128 |
| 0.0509 | 19.35 | 9600 | 0.0435 | 0.9853 | 0.7195 |
| 0.0482 | 20.16 | 10000 | 0.0451 | 0.9863 | 0.7170 |
| 0.0452 | 20.97 | 10400 | 0.0397 | 0.9874 | 0.7128 |
| 0.0438 | 21.77 | 10800 | 0.0378 | 0.9874 | 0.7108 |
| 0.0419 | 22.58 | 11200 | 0.0394 | 0.9881 | 0.7096 |
| 0.0389 | 23.39 | 11600 | 0.0412 | 0.9874 | 0.7105 |
| 0.0377 | 24.19 | 12000 | 0.0388 | 0.9847 | 0.7180 |
| 0.0362 | 25.0 | 12400 | 0.0365 | 0.9848 | 0.7149 |
| 0.0336 | 25.81 | 12800 | 0.0363 | 0.9840 | 0.7144 |
| 0.0315 | 26.61 | 13200 | 0.0366 | 0.9855 | 0.7138 |
| 0.031 | 27.42 | 13600 | 0.0381 | 0.9864 | 0.7171 |
| 0.0303 | 28.23 | 14000 | 0.0363 | 0.9857 | 0.7145 |
| 0.0276 | 29.03 | 14400 | 0.0365 | 0.9854 | 0.7136 |
| 0.0282 | 29.84 | 14800 | 0.0359 | 0.9853 | 0.7143 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 1.18.3
- Tokenizers 0.13.3
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