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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
base_model: bert-base-multilingual-cased
model-index:
- name: nlp-classification-comic-name-weighdecay-0.001-lr-1e-3
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. -->
# nlp-classification-comic-name-weighdecay-0.001-lr-1e-3
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0339
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9925
## 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: 0.00025
- train_batch_size: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| No log | 1.0 | 27 | 0.0356 | 0.0 | 0.0 | 0.0 | 0.9913 |
| No log | 2.0 | 54 | 0.0366 | 0.0 | 0.0 | 0.0 | 0.9921 |
| No log | 3.0 | 81 | 0.0345 | 0.0 | 0.0 | 0.0 | 0.9921 |
| No log | 4.0 | 108 | 0.0346 | 0.0 | 0.0 | 0.0 | 0.9921 |
| No log | 5.0 | 135 | 0.0341 | 0.0 | 0.0 | 0.0 | 0.9921 |
| No log | 6.0 | 162 | 0.0337 | 0.0 | 0.0 | 0.0 | 0.9921 |
| No log | 7.0 | 189 | 0.0345 | 0.0 | 0.0 | 0.0 | 0.9929 |
| No log | 8.0 | 216 | 0.0338 | 0.0 | 0.0 | 0.0 | 0.9925 |
| No log | 9.0 | 243 | 0.0338 | 0.0 | 0.0 | 0.0 | 0.9925 |
| No log | 10.0 | 270 | 0.0339 | 0.0 | 0.0 | 0.0 | 0.9925 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0 |