---
language:
- en
- ar
- bg
- de
- el
- fr
- hi
- ru
- es
- sw
- th
- tr
- ur
- vi
- zh
tags:
- generated_from_trainer
datasets:
- xnli
metrics:
- accuracy
model-index:
- name: pixel-base-finetuned-xnli-translate-train-all
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: XNLI
      type: xnli
      args: xnli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6254886211512718
---

<!-- 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. -->

# pixel-base-finetuned-xnli-translate-train-all

This model is a fine-tuned version of [Team-PIXEL/pixel-base](https://huggingface.co/Team-PIXEL/pixel-base) on the XNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8312
- Accuracy: 0.6255

## 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: 256
- eval_batch_size: 8
- seed: 555
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 50000
- mixed_precision_training: Apex, opt level O1

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0422        | 0.04  | 1000  | 1.0647          | 0.4250   |
| 0.9622        | 0.09  | 2000  | 1.0015          | 0.5051   |
| 0.93          | 0.13  | 3000  | 0.9750          | 0.5285   |
| 0.9126        | 0.17  | 4000  | 0.9396          | 0.5488   |
| 0.9033        | 0.22  | 5000  | 0.9353          | 0.5603   |
| 0.8861        | 0.26  | 6000  | 0.9369          | 0.5606   |
| 0.8799        | 0.3   | 7000  | 0.9407          | 0.5575   |
| 0.8627        | 0.35  | 8000  | 0.9079          | 0.5774   |
| 0.8658        | 0.39  | 9000  | 0.9110          | 0.5711   |
| 0.8521        | 0.43  | 10000 | 0.8945          | 0.5837   |
| 0.8562        | 0.48  | 11000 | 0.8818          | 0.5871   |
| 0.8479        | 0.52  | 12000 | 0.8771          | 0.5938   |
| 0.8451        | 0.56  | 13000 | 0.8965          | 0.5844   |
| 0.8433        | 0.61  | 14000 | 0.8814          | 0.5937   |
| 0.8331        | 0.65  | 15000 | 0.8721          | 0.5983   |
| 0.8267        | 0.7   | 16000 | 0.8691          | 0.5978   |
| 0.8254        | 0.74  | 17000 | 0.8646          | 0.5999   |
| 0.8214        | 0.78  | 18000 | 0.8700          | 0.6004   |
| 0.815         | 0.83  | 19000 | 0.8621          | 0.6016   |
| 0.8145        | 0.87  | 20000 | 0.8482          | 0.6119   |
| 0.8067        | 0.91  | 21000 | 0.8601          | 0.6053   |
| 0.8063        | 0.96  | 22000 | 0.8535          | 0.6093   |
| 0.8008        | 1.0   | 23000 | 0.8455          | 0.6123   |
| 0.7863        | 1.04  | 24000 | 0.8524          | 0.6107   |
| 0.7918        | 1.09  | 25000 | 0.8450          | 0.6142   |
| 0.7746        | 1.13  | 26000 | 0.8531          | 0.6095   |
| 0.7855        | 1.17  | 27000 | 0.8442          | 0.6150   |
| 0.7903        | 1.22  | 28000 | 0.8386          | 0.6162   |
| 0.7808        | 1.26  | 29000 | 0.8403          | 0.6178   |
| 0.7847        | 1.3   | 30000 | 0.8421          | 0.6145   |
| 0.7822        | 1.35  | 31000 | 0.8427          | 0.6157   |
| 0.769         | 1.39  | 32000 | 0.8397          | 0.6187   |
| 0.7822        | 1.43  | 33000 | 0.8315          | 0.6213   |
| 0.771         | 1.48  | 34000 | 0.8505          | 0.6141   |
| 0.7713        | 1.52  | 35000 | 0.8482          | 0.6142   |
| 0.7663        | 1.56  | 36000 | 0.8490          | 0.6169   |
| 0.7653        | 1.61  | 37000 | 0.8295          | 0.6229   |
| 0.7669        | 1.65  | 38000 | 0.8313          | 0.6217   |
| 0.77          | 1.69  | 39000 | 0.8309          | 0.6234   |
| 0.763         | 1.74  | 40000 | 0.8310          | 0.6256   |
| 0.7609        | 1.78  | 41000 | 0.8302          | 0.6228   |
| 0.7627        | 1.83  | 42000 | 0.8242          | 0.6269   |
| 0.7617        | 1.87  | 43000 | 0.8232          | 0.6264   |
| 0.7636        | 1.91  | 44000 | 0.8265          | 0.6261   |
| 0.7585        | 1.96  | 45000 | 0.8258          | 0.6268   |
| 0.7572        | 2.0   | 46000 | 0.8223          | 0.6278   |
| 0.7396        | 2.04  | 47000 | 0.8348          | 0.6242   |
| 0.7344        | 2.09  | 48000 | 0.8299          | 0.6270   |
| 0.7385        | 2.13  | 49000 | 0.8314          | 0.6240   |
| 0.7275        | 2.17  | 50000 | 0.8312          | 0.6255   |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0
- Datasets 2.0.0
- Tokenizers 0.12.1