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---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: unispeech-sat-base-digit-mask-ft
results: []
datasets:
- mazkooleg/digit_mask_augmented_raw
---
<!-- 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. -->
# unispeech-sat-base-digit-mask-ft
This model is a fine-tuned version of [microsoft/unispeech-sat-base](https://huggingface.co/microsoft/unispeech-sat-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0053
- Accuracy: 0.9991
- F1: 0.9991
## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Accuracy | F1 | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:------:|:---------------:|
| 0.0079 | 1.0 | 14264 | 0.9991 | 0.9991 | 0.0053 |
| 0.0019 | 2.0 | 28528 | 0.9987 | 0.9987 | 0.0078 |
| 0.0009 | 3.0 | 42792 | 0.9989 | 0.9989 | 0.0069 |
### Framework versions
- Transformers 4.28.1
- Pytorch 1.13.0+cpu
- Datasets 2.12.0
- Tokenizers 0.13.2 |