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---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- modernbert
- zeroshot
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: modernbert-zeroshot-xnli-eng-0.1
results: []
datasets:
- facebook/xnli
language:
- en
pipeline_tag: zero-shot-classification
---
<!-- 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. -->
# modernbert-zeroshot-xnli-eng-0.1
This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on 10% of the english subset of facebook/xnli dataset.
It achieves the following results on the evaluation set:
- Test Loss: 0.3539
- F1: 0.8596
## Model description
answerdotai/ModernBERT-base
## Intended uses & limitations
## Training and evaluation data
10% of the english subset of facebook/xnli dataset.
## Training procedure
trained on a single gpu for apx. 20 mins.
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- 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: 500
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.0801 | 0.1629 | 200 | 0.8987 | 0.5868 | 0.5820 | 0.6637 | 0.5868 |
| 0.6737 | 0.3257 | 400 | 0.4906 | 0.8184 | 0.8181 | 0.8340 | 0.8184 |
| 0.5361 | 0.4886 | 600 | 0.3931 | 0.8723 | 0.8724 | 0.8759 | 0.8723 |
| 0.4933 | 0.6515 | 800 | 0.3664 | 0.8782 | 0.8786 | 0.8853 | 0.8782 |
| 0.4728 | 0.8143 | 1000 | 0.4300 | 0.8303 | 0.8306 | 0.8604 | 0.8303 |
| 0.4434 | 0.9772 | 1200 | 0.3210 | 0.8922 | 0.8923 | 0.8925 | 0.8922 |
| 0.2859 | 1.1401 | 1400 | 0.3657 | 0.8483 | 0.8502 | 0.8651 | 0.8483 |
| 0.2768 | 1.3029 | 1600 | 0.4162 | 0.8403 | 0.8397 | 0.8520 | 0.8403 |
| 0.258 | 1.4658 | 1800 | 0.4072 | 0.8543 | 0.8543 | 0.8634 | 0.8543 |
| 0.2657 | 1.6287 | 2000 | 0.3763 | 0.8463 | 0.8460 | 0.8537 | 0.8463 |
| 0.2721 | 1.7915 | 2200 | 0.3940 | 0.8463 | 0.8464 | 0.8595 | 0.8463 |
| 0.2878 | 1.9544 | 2400 | 0.3539 | 0.8603 | 0.8596 | 0.8641 | 0.8603 |
| 0.1366 | 2.1173 | 2600 | 0.7444 | 0.8343 | 0.8371 | 0.8738 | 0.8343 |
### Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0 |