bif02/operons_function_family_conservation_string_511145

1---2library_name: transformers3license: mit4base_model: roberta-base5tags:6- generated_from_trainer7metrics:8- accuracy9model-index:10- name: operons_function_family_conservation_string_51114511  results: []12---13 14<!-- This model card has been generated automatically according to the information the Trainer had access to. You15should probably proofread and complete it, then remove this comment. -->16 17# operons_function_family_conservation_string_51114518 19This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.20It achieves the following results on the evaluation set:21- Loss: 0.357122- Accuracy: 0.860123 24## Model description25 26More information needed27 28## Intended uses & limitations29 30More information needed31 32## Training and evaluation data33 34More information needed35 36## Training procedure37 38### Training hyperparameters39 40The following hyperparameters were used during training:41- learning_rate: 3e-0542- train_batch_size: 3243- eval_batch_size: 3244- seed: 045- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments46- lr_scheduler_type: linear47- num_epochs: 1048 49### Training results50 51| Training Loss | Epoch | Step | Validation Loss | Accuracy |52|:-------------:|:-----:|:----:|:---------------:|:--------:|53| No log        | 1.0   | 161  | 0.4019          | 0.8374   |54| No log        | 2.0   | 322  | 0.3573          | 0.8601   |55| No log        | 3.0   | 483  | 0.3882          | 0.8497   |56| 0.4137        | 4.0   | 644  | 0.3756          | 0.8269   |57| 0.4137        | 5.0   | 805  | 0.3781          | 0.8374   |58| 0.4137        | 6.0   | 966  | 0.3479          | 0.8531   |59| 0.3429        | 7.0   | 1127 | 0.3835          | 0.8514   |60| 0.3429        | 8.0   | 1288 | 0.3676          | 0.8479   |61| 0.3429        | 9.0   | 1449 | 0.3699          | 0.8514   |62| 0.3077        | 10.0  | 1610 | 0.3768          | 0.8357   |63 64 65### Framework versions66 67- Transformers 5.0.068- Pytorch 2.10.0+cu12869- Datasets 4.0.070- Tokenizers 0.22.271