transformers safetensors roberta fill-mask generated_from_trainer autotrain_compatible endpoints_compatible region:us
---
tags:
- generated_from_trainer
model-index:
- name: AgglutiBERTa
  results: []
---

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

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 9.2646

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 10.1736       | 0.0   | 50   | 10.0949         |
| 9.8482        | 0.0   | 100  | 9.8180          |
| 9.6641        | 0.01  | 150  | 9.6621          |
| 9.6258        | 0.01  | 200  | 9.6023          |
| 9.5731        | 0.01  | 250  | 9.5421          |
| 9.5287        | 0.01  | 300  | 9.4865          |
| 9.4787        | 0.01  | 350  | 9.4386          |
| 9.3983        | 0.02  | 400  | 9.4157          |
| 9.4369        | 0.02  | 450  | 9.3807          |
| 9.3603        | 0.02  | 500  | 9.3665          |
| 9.3375        | 0.02  | 550  | 9.3334          |
| 9.3508        | 0.02  | 600  | 9.3293          |
| 9.3087        | 0.03  | 650  | 9.3008          |
| 9.3379        | 0.03  | 700  | 9.2867          |
| 9.3058        | 0.03  | 750  | 9.2872          |
| 9.2858        | 0.03  | 800  | 9.2779          |
| 9.3129        | 0.03  | 850  | 9.2670          |
| 9.2666        | 0.04  | 900  | 9.2695          |
| 9.3451        | 0.04  | 950  | 9.2661          |
| 9.3198        | 0.04  | 1000 | 9.2646          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
