---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- rouge
model-index:
- name: 43d4aa381d5eedf1cfc81e7ccbc49c88
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 43d4aa381d5eedf1cfc81e7ccbc49c88

This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on the nyu-mll/glue [mrpc] dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0078
- Data Size: 1.0
- Epoch Runtime: 5.2641
- Accuracy: 0.7783
- F1 Macro: 0.7466
- Rouge1: 0.7777
- Rouge2: 0.0
- Rougel: 0.7789
- Rougelsum: 0.7789

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Data Size | Epoch Runtime | Accuracy | F1 Macro | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------------:|:--------:|:--------:|:------:|:------:|:------:|:---------:|
| No log        | 0     | 0    | 0.7135          | 0         | 1.0609        | 0.3314   | 0.2496   | 0.3308 | 0.0    | 0.3317 | 0.3314    |
| No log        | 1     | 114  | 0.6662          | 0.0078    | 1.3643        | 0.6651   | 0.3994   | 0.6657 | 0.0    | 0.6645 | 0.6651    |
| No log        | 2     | 228  | 0.6408          | 0.0156    | 1.4235        | 0.6651   | 0.3994   | 0.6657 | 0.0    | 0.6645 | 0.6651    |
| No log        | 3     | 342  | 0.6388          | 0.0312    | 1.6159        | 0.6651   | 0.3994   | 0.6657 | 0.0    | 0.6645 | 0.6651    |
| 0.0205        | 4     | 456  | 0.6150          | 0.0625    | 1.9014        | 0.6745   | 0.4306   | 0.6751 | 0.0    | 0.6745 | 0.6745    |
| 0.0205        | 5     | 570  | 0.6034          | 0.125     | 2.0959        | 0.6869   | 0.4818   | 0.6869 | 0.0    | 0.6869 | 0.6869    |
| 0.0205        | 6     | 684  | 0.5188          | 0.25      | 2.6063        | 0.7417   | 0.6524   | 0.7417 | 0.0    | 0.7417 | 0.7417    |
| 0.1345        | 7     | 798  | 0.4405          | 0.5       | 3.4198        | 0.8001   | 0.7643   | 0.7995 | 0.0    | 0.8001 | 0.8007    |
| 0.3533        | 8.0   | 912  | 0.4843          | 1.0       | 5.1439        | 0.7848   | 0.7230   | 0.7848 | 0.0    | 0.7854 | 0.7854    |
| 0.165         | 9.0   | 1026 | 0.6949          | 1.0       | 5.1065        | 0.7830   | 0.7197   | 0.7824 | 0.0    | 0.7830 | 0.7836    |
| 0.1128        | 10.0  | 1140 | 0.7659          | 1.0       | 5.1628        | 0.7978   | 0.7537   | 0.7983 | 0.0    | 0.7983 | 0.7981    |
| 0.0761        | 11.0  | 1254 | 1.0078          | 1.0       | 5.2641        | 0.7783   | 0.7466   | 0.7777 | 0.0    | 0.7789 | 0.7789    |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.1