---
license: apache-2.0
base_model: Flamenco43/NanoBERT_V4
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: NanoBertV1Step800k-CNER
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/nananansnsns/LLLM/runs/7w1o84kw)
# NanoBertV1Step800k-CNER

This model is a fine-tuned version of [Flamenco43/NanoBERT_V4](https://huggingface.co/Flamenco43/NanoBERT_V4) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0188
- Precision: 0.9049
- Recall: 0.9199
- F1: 0.9123
- Accuracy: 0.9942

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0264        | 1.0   | 2000 | 0.0257          | 0.8680    | 0.8749 | 0.8714 | 0.9917   |
| 0.0157        | 2.0   | 4000 | 0.0204          | 0.8834    | 0.9163 | 0.8995 | 0.9934   |
| 0.0092        | 3.0   | 6000 | 0.0188          | 0.9049    | 0.9199 | 0.9123 | 0.9942   |
| 0.0047        | 4.0   | 8000 | 0.0219          | 0.9041    | 0.9269 | 0.9153 | 0.9944   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1