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---
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library_name: transformers
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tags:
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- generated_from_trainer
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metrics:
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- f1
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- accuracy
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- precision
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- recall
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model-index:
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- name: ModernBERT-large-nli-clf
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results: []
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datasets:
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- param-bharat/scorers-nli
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base_model:
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- answerdotai/ModernBERT-large
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pipeline_tag: text-classification
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# ModernBERT-large-nli-clf |
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This model was trained from scratch on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0124 |
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- F1: 0.7754 |
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- Accuracy: 0.7754 |
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- Precision: 0.7754 |
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- Recall: 0.7754 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 64 |
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- eval_batch_size: 128 |
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- seed: 2024 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 512 |
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- total_eval_batch_size: 1024 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall | |
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|:-------------:|:------:|:-----:|:---------------:|:------:|:--------:|:---------:|:------:| |
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| No log | 0 | 0 | 0.0114 | 0.8209 | 0.821 | 0.8211 | 0.821 | |
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| 0.0103 | 0.3000 | 7956 | 0.0116 | 0.8576 | 0.8589 | 0.8705 | 0.8589 | |
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| 0.0091 | 0.5999 | 15912 | 0.0091 | 0.8945 | 0.8945 | 0.8945 | 0.8945 | |
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| 0.0097 | 0.8999 | 23868 | 0.0096 | 0.8874 | 0.8874 | 0.8880 | 0.8874 | |
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| 0.0078 | 1.1999 | 31824 | 0.0088 | 0.8957 | 0.8957 | 0.8957 | 0.8957 | |
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| 0.0174 | 1.4998 | 39780 | 0.0174 | 0.6024 | 0.6113 | 0.6195 | 0.6113 | |
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| 0.0136 | 1.7998 | 47736 | 0.0134 | 0.7344 | 0.7344 | 0.7344 | 0.7344 | |
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| 0.0129 | 2.0998 | 55692 | 0.0131 | 0.7370 | 0.7408 | 0.7531 | 0.7408 | |
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| 0.0125 | 2.3997 | 63648 | 0.0125 | 0.7530 | 0.753 | 0.7530 | 0.753 | |
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| 0.0129 | 2.6997 | 71604 | 0.0124 | 0.7724 | 0.7724 | 0.7724 | 0.7724 | |
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| 0.0125 | 2.9997 | 79560 | 0.0124 | 0.7754 | 0.7754 | 0.7754 | 0.7754 | |
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### Framework versions |
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- Transformers 4.48.0.dev0 |
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- Pytorch 2.5.1 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
