---
license: apache-2.0
base_model: google-bert/bert-base-cased
tags:
- generated_from_trainer
model-index:
- name: bert-base-cased
  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. -->

# bert-base-cased

This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1793
- Icm: 0.1480
- Icmnorm: 0.5752
- Fmeasure: 0.7194

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 9
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Icm    | Icmnorm | Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 193  | 0.6062          | 0.0275 | 0.5140  | 0.6639   |
| No log        | 2.0   | 386  | 0.5694          | 0.0336 | 0.5171  | 0.6785   |
| 0.5724        | 3.0   | 579  | 0.8413          | 0.0158 | 0.5080  | 0.6641   |
| 0.5724        | 4.0   | 772  | 1.1793          | 0.1480 | 0.5752  | 0.7194   |
| 0.5724        | 5.0   | 965  | 1.4878          | 0.0672 | 0.5341  | 0.6892   |
| 0.2239        | 6.0   | 1158 | 1.6802          | 0.0966 | 0.5491  | 0.7019   |
| 0.2239        | 7.0   | 1351 | 1.8348          | 0.0799 | 0.5406  | 0.6964   |
| 0.0665        | 8.0   | 1544 | 1.9795          | 0.0606 | 0.5308  | 0.6897   |
| 0.0665        | 9.0   | 1737 | 2.0300          | 0.0606 | 0.5308  | 0.6897   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2