---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ssr-360m
  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. -->

# ssr-360m

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0227
- Model Preparation Time: 0.0066
- Wer: 0.1206

## 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: 0.0005
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 10
- total_train_batch_size: 20
- 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
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Model Preparation Time | Wer    |
|:-------------:|:------:|:-----:|:---------------:|:----------------------:|:------:|
| 12.0652       | 0.9999 | 5200  | 0.5135          | 0.0066                 | 0.4332 |
| 2.1537        | 1.9999 | 10400 | 0.0530          | 0.0066                 | 0.1585 |
| 3.0568        | 2.9999 | 15600 | 0.0731          | 0.0066                 | 0.2030 |
| 0.9142        | 3.9999 | 20800 | 0.0313          | 0.0066                 | 0.1407 |
| 0.3436        | 4.9999 | 26000 | 0.0308          | 0.0066                 | 0.1403 |
| 0.7558        | 5.9999 | 31200 | 0.0286          | 0.0066                 | 0.1337 |
| 0.5733        | 6.9999 | 36400 | 0.0265          | 0.0066                 | 0.1221 |
| 0.1573        | 7.9999 | 41600 | 0.0241          | 0.0066                 | 0.1439 |
| 0.2248        | 8.9999 | 46800 | 0.0225          | 0.0066                 | 0.1199 |
| 0.1501        | 9.9999 | 52000 | 0.0227          | 0.0066                 | 0.1206 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1
- Datasets 3.3.2
- Tokenizers 0.21.0