---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: bert-base-multilingual-cased-amh
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-multilingual-cased-amh

This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1213
- Accuracy: 0.6854
- F1 Binary: 0.4627
- Precision: 0.3422
- Recall: 0.7141

## 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: 3e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 53
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Binary | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:---------:|:------:|
| No log        | 1.0   | 267  | 0.1291          | 0.4986   | 0.4145    | 0.2662    | 0.9356 |
| 0.124         | 2.0   | 534  | 0.1251          | 0.7129   | 0.4703    | 0.3618    | 0.6720 |
| 0.124         | 3.0   | 801  | 0.1221          | 0.6709   | 0.4591    | 0.3335    | 0.7364 |
| 0.114         | 4.0   | 1068 | 0.1213          | 0.6854   | 0.4627    | 0.3422    | 0.7141 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0