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---
license: apache-2.0
tags:
- generated_from_trainer
- pt
- robust-speech-event
datasets:
- common_voice
model-index:
- name: sew-tiny-portuguese-cv
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. -->
# sew-tiny-portuguese-cv
This model is a fine-tuned version of [lgris/sew-tiny-pt](https://huggingface.co/lgris/sew-tiny-pt) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5110
- Wer: 0.2842
## 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
- gradient_accumulation_steps: 4
- 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: 1000
- training_steps: 40000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| No log | 4.92 | 1000 | 0.8468 | 0.6494 |
| 3.4638 | 9.85 | 2000 | 0.4978 | 0.3815 |
| 3.4638 | 14.78 | 3000 | 0.4734 | 0.3417 |
| 0.9904 | 19.7 | 4000 | 0.4577 | 0.3344 |
| 0.9904 | 24.63 | 5000 | 0.4376 | 0.3170 |
| 0.8849 | 29.55 | 6000 | 0.4225 | 0.3118 |
| 0.8849 | 34.48 | 7000 | 0.4354 | 0.3080 |
| 0.819 | 39.41 | 8000 | 0.4434 | 0.3004 |
| 0.819 | 44.33 | 9000 | 0.4710 | 0.3132 |
| 0.7706 | 49.26 | 10000 | 0.4497 | 0.3064 |
| 0.7706 | 54.19 | 11000 | 0.4598 | 0.3100 |
| 0.7264 | 59.11 | 12000 | 0.4271 | 0.3013 |
| 0.7264 | 64.04 | 13000 | 0.4333 | 0.2959 |
| 0.6909 | 68.96 | 14000 | 0.4554 | 0.3019 |
| 0.6909 | 73.89 | 15000 | 0.4444 | 0.2888 |
| 0.6614 | 78.81 | 16000 | 0.4734 | 0.3081 |
| 0.6614 | 83.74 | 17000 | 0.4820 | 0.3058 |
| 0.6379 | 88.67 | 18000 | 0.4416 | 0.2950 |
| 0.6379 | 93.59 | 19000 | 0.4614 | 0.2974 |
| 0.6055 | 98.52 | 20000 | 0.4812 | 0.3018 |
| 0.6055 | 103.45 | 21000 | 0.4700 | 0.3018 |
| 0.5823 | 108.37 | 22000 | 0.4726 | 0.2999 |
| 0.5823 | 113.3 | 23000 | 0.4979 | 0.2887 |
| 0.5597 | 118.23 | 24000 | 0.4813 | 0.2980 |
| 0.5597 | 123.15 | 25000 | 0.4968 | 0.2972 |
| 0.542 | 128.08 | 26000 | 0.5331 | 0.3059 |
| 0.542 | 133.0 | 27000 | 0.5046 | 0.2978 |
| 0.5185 | 137.93 | 28000 | 0.4882 | 0.2922 |
| 0.5185 | 142.85 | 29000 | 0.4945 | 0.2938 |
| 0.499 | 147.78 | 30000 | 0.4971 | 0.2913 |
| 0.499 | 152.71 | 31000 | 0.4948 | 0.2873 |
| 0.4811 | 157.63 | 32000 | 0.4924 | 0.2918 |
| 0.4811 | 162.56 | 33000 | 0.5128 | 0.2911 |
| 0.4679 | 167.49 | 34000 | 0.5098 | 0.2892 |
| 0.4679 | 172.41 | 35000 | 0.4966 | 0.2863 |
| 0.456 | 177.34 | 36000 | 0.5033 | 0.2839 |
| 0.456 | 182.27 | 37000 | 0.5114 | 0.2875 |
| 0.4453 | 187.19 | 38000 | 0.5154 | 0.2859 |
| 0.4453 | 192.12 | 39000 | 0.5102 | 0.2847 |
| 0.4366 | 197.04 | 40000 | 0.5110 | 0.2842 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0
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