transformers tensorboard safetensors bert fill-mask generated_from_trainer base_model:bert-large-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
tags:
- generated_from_trainer
base_model: bert-large-uncased
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](https://huggingface.co/bert-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3395

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.4213        | 1.0   | 25   | 3.2802          |
| 3.1204        | 2.0   | 50   | 2.8289          |
| 2.7337        | 3.0   | 75   | 2.5070          |
| 2.4701        | 4.0   | 100  | 2.1833          |
| 2.2536        | 5.0   | 125  | 2.0859          |
| 2.1284        | 6.0   | 150  | 2.0973          |
| 1.9703        | 7.0   | 175  | 1.8079          |
| 1.9372        | 8.0   | 200  | 1.8733          |
| 1.9115        | 9.0   | 225  | 1.7319          |
| 1.7705        | 10.0  | 250  | 1.8154          |
| 1.7454        | 11.0  | 275  | 1.6135          |
| 1.7338        | 12.0  | 300  | 1.6072          |
| 1.6741        | 13.0  | 325  | 1.4479          |
| 1.6552        | 14.0  | 350  | 1.6893          |
| 1.5546        | 15.0  | 375  | 1.5714          |
| 1.5905        | 16.0  | 400  | 1.6661          |
| 1.5136        | 17.0  | 425  | 1.6100          |
| 1.5403        | 18.0  | 450  | 1.5664          |
| 1.4947        | 19.0  | 475  | 1.4803          |
| 1.4654        | 20.0  | 500  | 1.6041          |
| 1.4449        | 21.0  | 525  | 1.4071          |
| 1.4817        | 22.0  | 550  | 1.5543          |
| 1.377         | 23.0  | 575  | 1.3897          |
| 1.4102        | 24.0  | 600  | 1.4572          |
| 1.3246        | 25.0  | 625  | 1.5699          |
| 1.3323        | 26.0  | 650  | 1.4316          |
| 1.2745        | 27.0  | 675  | 1.5004          |
| 1.2589        | 28.0  | 700  | 1.5209          |
| 1.3488        | 29.0  | 725  | 1.4734          |
| 1.301         | 30.0  | 750  | 1.5197          |
| 1.2824        | 31.0  | 775  | 1.5087          |
| 1.2771        | 32.0  | 800  | 1.4041          |
| 1.2794        | 33.0  | 825  | 1.5773          |
| 1.2343        | 34.0  | 850  | 1.3722          |
| 1.3235        | 35.0  | 875  | 1.5125          |
| 1.2567        | 36.0  | 900  | 1.3877          |
| 1.2682        | 37.0  | 925  | 1.5471          |
| 1.2028        | 38.0  | 950  | 1.3677          |
| 1.2059        | 39.0  | 975  | 1.4233          |
| 1.2103        | 40.0  | 1000 | 1.5361          |
| 1.1987        | 41.0  | 1025 | 1.5492          |
| 1.2853        | 42.0  | 1050 | 1.4274          |
| 1.2088        | 43.0  | 1075 | 1.5027          |
| 1.2573        | 44.0  | 1100 | 1.5138          |
| 1.2511        | 45.0  | 1125 | 1.4198          |
| 1.1932        | 46.0  | 1150 | 1.3065          |
| 1.1864        | 47.0  | 1175 | 1.4521          |
| 1.2362        | 48.0  | 1200 | 1.4576          |
| 1.215         | 49.0  | 1225 | 1.4246          |
| 1.2118        | 50.0  | 1250 | 1.3395          |


### Framework versions

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