---
license: apache-2.0
base_model: bert-large-uncased-whole-word-masking
tags:
- generated_from_trainer
model-index:
- name: pictalk
  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. -->

# pictalk

This model is a fine-tuned version of [bert-large-uncased-whole-word-masking](https://huggingface.co/bert-large-uncased-whole-word-masking) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5286

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.2507        | 1.0   | 25   | 2.7433          |
| 2.518         | 2.0   | 50   | 2.2772          |
| 2.323         | 3.0   | 75   | 2.0185          |
| 2.0883        | 4.0   | 100  | 1.9731          |
| 1.8835        | 5.0   | 125  | 1.9086          |
| 1.8641        | 6.0   | 150  | 1.7880          |
| 1.7244        | 7.0   | 175  | 1.7763          |
| 1.7395        | 8.0   | 200  | 1.7191          |
| 1.6834        | 9.0   | 225  | 1.6734          |
| 1.6631        | 10.0  | 250  | 1.6970          |
| 1.5764        | 11.0  | 275  | 1.6939          |
| 1.54          | 12.0  | 300  | 1.6576          |
| 1.5205        | 13.0  | 325  | 1.5530          |
| 1.4832        | 14.0  | 350  | 1.5448          |
| 1.4582        | 15.0  | 375  | 1.6000          |
| 1.418         | 16.0  | 400  | 1.5240          |
| 1.4152        | 17.0  | 425  | 1.5330          |
| 1.3529        | 18.0  | 450  | 1.5850          |
| 1.3886        | 19.0  | 475  | 1.4814          |
| 1.3268        | 20.0  | 500  | 1.6087          |
| 1.2914        | 21.0  | 525  | 1.5714          |
| 1.3431        | 22.0  | 550  | 1.4989          |
| 1.2838        | 23.0  | 575  | 1.5934          |
| 1.2943        | 24.0  | 600  | 1.4751          |
| 1.2704        | 25.0  | 625  | 1.5158          |
| 1.284         | 26.0  | 650  | 1.6148          |
| 1.2148        | 27.0  | 675  | 1.4828          |
| 1.2382        | 28.0  | 700  | 1.4890          |
| 1.1684        | 29.0  | 725  | 1.5531          |
| 1.2053        | 30.0  | 750  | 1.4755          |
| 1.1973        | 31.0  | 775  | 1.4426          |
| 1.2127        | 32.0  | 800  | 1.5464          |
| 1.1802        | 33.0  | 825  | 1.4410          |
| 1.1828        | 34.0  | 850  | 1.5026          |
| 1.1338        | 35.0  | 875  | 1.5691          |
| 1.11          | 36.0  | 900  | 1.5073          |
| 1.1456        | 37.0  | 925  | 1.5055          |
| 1.1253        | 38.0  | 950  | 1.5108          |
| 1.1214        | 39.0  | 975  | 1.4563          |
| 1.1654        | 40.0  | 1000 | 1.5881          |
| 1.0921        | 41.0  | 1025 | 1.4060          |
| 1.1087        | 42.0  | 1050 | 1.4952          |
| 1.0824        | 43.0  | 1075 | 1.5512          |
| 1.1127        | 44.0  | 1100 | 1.5481          |
| 1.0994        | 45.0  | 1125 | 1.5692          |
| 1.0579        | 46.0  | 1150 | 1.4802          |
| 1.1006        | 47.0  | 1175 | 1.5585          |
| 1.0692        | 48.0  | 1200 | 1.4303          |
| 1.1131        | 49.0  | 1225 | 1.5129          |
| 1.0943        | 50.0  | 1250 | 1.5286          |


### Framework versions

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