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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: answerdotai/ModernBERT-base |
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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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datasets: |
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- param-bharat/scorers-nli |
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pipeline_tag: text-classification |
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model-index: |
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- name: ModernBERT-base-nli-clf |
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results: [] |
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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-base-nli-clf |
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This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0101 |
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- F1: 0.8717 |
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- Accuracy: 0.8717 |
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- Precision: 0.8717 |
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- Recall: 0.8717 |
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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: 128 |
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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: 1024 |
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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: 5 |
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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 | 0.0185 | 0.5044 | 0.5297 | 0.5418 | 0.5297 | |
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| 0.0135 | 0.4999 | 6630 | 0.0150 | 0.7539 | 0.755 | 0.7582 | 0.755 | |
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| 0.0108 | 0.9998 | 13260 | 0.0108 | 0.8539 | 0.8539 | 0.8540 | 0.8539 | |
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| 0.0109 | 1.4998 | 19890 | 0.0113 | 0.8492 | 0.8493 | 0.8496 | 0.8493 | |
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| 0.0103 | 1.9997 | 26520 | 0.0103 | 0.8641 | 0.8641 | 0.8641 | 0.8641 | |
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| 0.0099 | 2.4996 | 33150 | 0.0109 | 0.8575 | 0.8579 | 0.8630 | 0.8579 | |
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| 0.0095 | 2.9995 | 39780 | 0.0103 | 0.8686 | 0.8686 | 0.8686 | 0.8686 | |
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| 0.0092 | 3.4995 | 46410 | 0.0101 | 0.8700 | 0.87 | 0.8700 | 0.87 | |
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| 0.0094 | 3.9994 | 53040 | 0.0097 | 0.8751 | 0.8751 | 0.8751 | 0.8751 | |
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| 0.0095 | 4.4993 | 59670 | 0.0105 | 0.8664 | 0.8664 | 0.8664 | 0.8664 | |
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| 0.0086 | 4.9992 | 66300 | 0.0101 | 0.8717 | 0.8717 | 0.8717 | 0.8717 | |
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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 |
