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---
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 |