transformers safetensors roberta text-classification generated_from_trainer base_model:shanhy/furina_clir_seed12_cross_translation_augmentation_0.1val base_model:finetune:shanhy/furina_clir_seed12_cross_translation_augmentation_0.1val autotrain_compatible endpoints_compatible region:us
---
base_model: shanhy/furina_clir_seed12_cross_translation_augmentation_0.1val
tags:
- generated_from_trainer
model-index:
- name: furina_clir_seed12_cross_translation_augmentation_0.1val_continuous
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# furina_clir_seed12_cross_translation_augmentation_0.1val_continuous

This model is a fine-tuned version of [shanhy/furina_clir_seed12_cross_translation_augmentation_0.1val](https://huggingface.co/shanhy/furina_clir_seed12_cross_translation_augmentation_0.1val) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0185
- Spearman Corr: 0.8059

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 128
- seed: 12
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Spearman Corr |
|:-------------:|:-----:|:----:|:---------------:|:-------------:|
| No log        | 0.54  | 200  | 0.0222          | 0.7614        |
| No log        | 1.08  | 400  | 0.0214          | 0.7711        |
| No log        | 1.62  | 600  | 0.0215          | 0.7712        |
| 0.0112        | 2.15  | 800  | 0.0207          | 0.7794        |
| 0.0112        | 2.69  | 1000 | 0.0204          | 0.7832        |
| 0.0112        | 3.23  | 1200 | 0.0208          | 0.7833        |
| 0.0112        | 3.77  | 1400 | 0.0198          | 0.7875        |
| 0.007         | 4.31  | 1600 | 0.0200          | 0.7888        |
| 0.007         | 4.85  | 1800 | 0.0195          | 0.7924        |
| 0.007         | 5.38  | 2000 | 0.0196          | 0.7899        |
| 0.007         | 5.92  | 2200 | 0.0198          | 0.7925        |
| 0.0053        | 6.46  | 2400 | 0.0197          | 0.7936        |
| 0.0053        | 7.0   | 2600 | 0.0190          | 0.7979        |
| 0.0053        | 7.54  | 2800 | 0.0188          | 0.8015        |
| 0.0047        | 8.08  | 3000 | 0.0189          | 0.8032        |
| 0.0047        | 8.61  | 3200 | 0.0191          | 0.8023        |
| 0.0047        | 9.15  | 3400 | 0.0183          | 0.8056        |
| 0.0047        | 9.69  | 3600 | 0.0185          | 0.8059        |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
