---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ssc-sco-w2vbase-model
  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. -->

# ssc-sco-w2vbase-model

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2065
- Cer: 0.9997
- Wer: 1.0

## 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: 0.001
- train_batch_size: 2
- eval_batch_size: 12
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer    | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|:---:|
| 3.002         | 1.9231 | 200  | 3.2523          | 0.9997 | 1.0 |
| 3.0059        | 3.8462 | 400  | 3.2065          | 0.9997 | 1.0 |


### Framework versions

- Transformers 4.52.1
- Pytorch 2.9.1+cu128
- Datasets 3.6.0
- Tokenizers 0.21.4