---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: ModernBERT-large-nli-clf
  results: []
datasets:
- param-bharat/scorers-nli
base_model:
- answerdotai/ModernBERT-large
pipeline_tag: text-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-large-nli-clf

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0124
- F1: 0.7754
- Accuracy: 0.7754
- Precision: 0.7754
- Recall: 0.7754

## 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: 0.0003
- train_batch_size: 64
- eval_batch_size: 128
- seed: 2024
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 512
- total_eval_batch_size: 1024
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | F1     | Accuracy | Precision | Recall |
|:-------------:|:------:|:-----:|:---------------:|:------:|:--------:|:---------:|:------:|
| No log        | 0      | 0     | 0.0114          | 0.8209 | 0.821    | 0.8211    | 0.821  |
| 0.0103        | 0.3000 | 7956  | 0.0116          | 0.8576 | 0.8589   | 0.8705    | 0.8589 |
| 0.0091        | 0.5999 | 15912 | 0.0091          | 0.8945 | 0.8945   | 0.8945    | 0.8945 |
| 0.0097        | 0.8999 | 23868 | 0.0096          | 0.8874 | 0.8874   | 0.8880    | 0.8874 |
| 0.0078        | 1.1999 | 31824 | 0.0088          | 0.8957 | 0.8957   | 0.8957    | 0.8957 |
| 0.0174        | 1.4998 | 39780 | 0.0174          | 0.6024 | 0.6113   | 0.6195    | 0.6113 |
| 0.0136        | 1.7998 | 47736 | 0.0134          | 0.7344 | 0.7344   | 0.7344    | 0.7344 |
| 0.0129        | 2.0998 | 55692 | 0.0131          | 0.7370 | 0.7408   | 0.7531    | 0.7408 |
| 0.0125        | 2.3997 | 63648 | 0.0125          | 0.7530 | 0.753    | 0.7530    | 0.753  |
| 0.0129        | 2.6997 | 71604 | 0.0124          | 0.7724 | 0.7724   | 0.7724    | 0.7724 |
| 0.0125        | 2.9997 | 79560 | 0.0124          | 0.7754 | 0.7754   | 0.7754    | 0.7754 |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.21.0