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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-1
results: []
---
<!-- 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. -->
# wav2vec2-1
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8870
- Wer: 0.3805
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.6457 | 0.5 | 500 | 2.8866 | 0.9999 |
| 2.863 | 1.0 | 1000 | 2.8676 | 1.0 |
| 1.8085 | 1.5 | 1500 | 0.9396 | 0.6602 |
| 0.8828 | 2.0 | 2000 | 0.7278 | 0.5699 |
| 0.6659 | 2.5 | 2500 | 0.7000 | 0.5401 |
| 0.6085 | 3.0 | 3000 | 0.7143 | 0.4939 |
| 0.4878 | 3.5 | 3500 | 0.5845 | 0.4717 |
| 0.4888 | 4.0 | 4000 | 0.6201 | 0.4677 |
| 0.4022 | 4.5 | 4500 | 0.5984 | 0.4532 |
| 0.3947 | 5.0 | 5000 | 0.5874 | 0.4378 |
| 0.3415 | 5.5 | 5500 | 0.6486 | 0.4405 |
| 0.3413 | 6.0 | 6000 | 0.5988 | 0.4355 |
| 0.2903 | 6.5 | 6500 | 0.6584 | 0.4304 |
| 0.3046 | 7.0 | 7000 | 0.6602 | 0.4189 |
| 0.2625 | 7.5 | 7500 | 0.5924 | 0.4235 |
| 0.2625 | 8.0 | 8000 | 0.6541 | 0.4212 |
| 0.2341 | 8.5 | 8500 | 0.6365 | 0.4171 |
| 0.2384 | 9.0 | 9000 | 0.6095 | 0.4182 |
| 0.2052 | 9.5 | 9500 | 0.6675 | 0.4091 |
| 0.2124 | 10.0 | 10000 | 0.6524 | 0.4110 |
| 0.1915 | 10.5 | 10500 | 0.6877 | 0.4122 |
| 0.1922 | 11.0 | 11000 | 0.6857 | 0.4122 |
| 0.1719 | 11.5 | 11500 | 0.6881 | 0.4056 |
| 0.1811 | 12.0 | 12000 | 0.6832 | 0.4083 |
| 0.1554 | 12.5 | 12500 | 0.7378 | 0.4103 |
| 0.163 | 13.0 | 13000 | 0.6940 | 0.4019 |
| 0.1452 | 13.5 | 13500 | 0.6811 | 0.3993 |
| 0.1457 | 14.0 | 14000 | 0.7216 | 0.4007 |
| 0.1319 | 14.5 | 14500 | 0.7243 | 0.3996 |
| 0.1367 | 15.0 | 15000 | 0.7332 | 0.4006 |
| 0.118 | 15.5 | 15500 | 0.7609 | 0.4050 |
| 0.121 | 16.0 | 16000 | 0.7585 | 0.4021 |
| 0.1096 | 16.5 | 16500 | 0.7583 | 0.4003 |
| 0.112 | 17.0 | 17000 | 0.7928 | 0.4011 |
| 0.1063 | 17.5 | 17500 | 0.7794 | 0.4038 |
| 0.1009 | 18.0 | 18000 | 0.7474 | 0.3982 |
| 0.0931 | 18.5 | 18500 | 0.8143 | 0.3980 |
| 0.0943 | 19.0 | 19000 | 0.7873 | 0.4000 |
| 0.0847 | 19.5 | 19500 | 0.8064 | 0.3991 |
| 0.0831 | 20.0 | 20000 | 0.8564 | 0.3967 |
| 0.0821 | 20.5 | 20500 | 0.8632 | 0.3956 |
| 0.0807 | 21.0 | 21000 | 0.8250 | 0.3928 |
| 0.0748 | 21.5 | 21500 | 0.8389 | 0.3949 |
| 0.0751 | 22.0 | 22000 | 0.8355 | 0.3943 |
| 0.072 | 22.5 | 22500 | 0.8568 | 0.3930 |
| 0.0696 | 23.0 | 23000 | 0.8396 | 0.3912 |
| 0.0678 | 23.5 | 23500 | 0.8634 | 0.3901 |
| 0.0671 | 24.0 | 24000 | 0.8576 | 0.3880 |
| 0.063 | 24.5 | 24500 | 0.8303 | 0.3876 |
| 0.0575 | 25.0 | 25000 | 0.9125 | 0.3847 |
| 0.0572 | 25.5 | 25500 | 0.8745 | 0.3839 |
| 0.0572 | 26.0 | 26000 | 0.8714 | 0.3844 |
| 0.0533 | 26.5 | 26500 | 0.8824 | 0.3840 |
| 0.0496 | 27.0 | 27000 | 0.8993 | 0.3830 |
| 0.0525 | 27.5 | 27500 | 0.8818 | 0.3830 |
| 0.0514 | 28.0 | 28000 | 0.8874 | 0.3819 |
| 0.0464 | 28.5 | 28500 | 0.8947 | 0.3802 |
| 0.0473 | 29.0 | 29000 | 0.9028 | 0.3805 |
| 0.048 | 29.5 | 29500 | 0.8899 | 0.3801 |
| 0.0458 | 30.0 | 30000 | 0.8870 | 0.3805 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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