tab7v/ent_description

1---2library_name: transformers3base_model: textattack/bert-base-uncased-CoLA4tags:5- generated_from_trainer6model-index:7- name: ent_description8  results: []9---10 11<!-- This model card has been generated automatically according to the information the Trainer had access to. You12should probably proofread and complete it, then remove this comment. -->13 14# ent_description15 16This model is a fine-tuned version of [textattack/bert-base-uncased-CoLA](https://huggingface.co/textattack/bert-base-uncased-CoLA) on an unknown dataset.17It achieves the following results on the evaluation set:18- Loss: 0.658019- Class Acc: 0.929220- Class Rec: 0.841321- Class Prec: 0.828122- Class F1: 0.834623- Class Mcc: 0.789624- Feature Ham Loss: 0.219225- Feature Rec: 0.812326- Feature Prec: 0.841727- Feature F1: 0.824228 29## Model description30 31More information needed32 33## Intended uses & limitations34 35More information needed36 37## Training and evaluation data38 39More information needed40 41## Training procedure42 43### Training hyperparameters44 45The following hyperparameters were used during training:46- learning_rate: 0.000147- train_batch_size: 3248- eval_batch_size: 3249- seed: 4250- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments51- lr_scheduler_type: linear52- num_epochs: 2053 54### Training results55 56| Training Loss | Epoch | Step | Validation Loss | Class Acc | Class Rec | Class Prec | Class F1 | Class Mcc | Feature Ham Loss | Feature Rec | Feature Prec | Feature F1 |57|:-------------:|:-----:|:----:|:---------------:|:---------:|:---------:|:----------:|:--------:|:---------:|:----------------:|:-----------:|:------------:|:----------:|58| No log        | 1.0   | 44   | 0.7838          | 0.8617    | 0.3571    | 0.9783     | 0.5233   | 0.5429    | 0.2437           | 0.8232      | 0.8093       | 0.8085     |59| No log        | 2.0   | 88   | 0.6784          | 0.9258    | 0.7222    | 0.91       | 0.8053   | 0.7680    | 0.2626           | 0.7303      | 0.8361       | 0.7713     |60| No log        | 3.0   | 132  | 0.7053          | 0.8870    | 0.9206    | 0.6705     | 0.7759   | 0.7186    | 0.2175           | 0.9294      | 0.7970       | 0.8501     |61| No log        | 4.0   | 176  | 0.7280          | 0.8853    | 0.9286    | 0.6648     | 0.7748   | 0.7183    | 0.2226           | 0.9313      | 0.7921       | 0.8499     |62| No log        | 5.0   | 220  | 0.6285          | 0.9376    | 0.7540    | 0.9406     | 0.8370   | 0.8065    | 0.2310           | 0.7869      | 0.8440       | 0.8071     |63| No log        | 6.0   | 264  | 0.6029          | 0.9342    | 0.8095    | 0.8718     | 0.8395   | 0.7991    | 0.2293           | 0.8327      | 0.8206       | 0.8230     |64| No log        | 7.0   | 308  | 0.6106          | 0.9410    | 0.8333    | 0.8824     | 0.8571   | 0.8205    | 0.2146           | 0.8810      | 0.8181       | 0.8371     |65| No log        | 8.0   | 352  | 0.6012          | 0.9410    | 0.8333    | 0.8824     | 0.8571   | 0.8205    | 0.2104           | 0.8734      | 0.8242       | 0.8390     |66| No log        | 9.0   | 396  | 0.5981          | 0.9376    | 0.8413    | 0.8618     | 0.8514   | 0.8120    | 0.2087           | 0.8632      | 0.8290       | 0.8387     |67| No log        | 10.0  | 440  | 0.6213          | 0.9393    | 0.8175    | 0.8879     | 0.8512   | 0.8143    | 0.2323           | 0.7704      | 0.8491       | 0.8029     |68| No log        | 11.0  | 484  | 0.6667          | 0.9258    | 0.8968    | 0.7847     | 0.8370   | 0.7922    | 0.2243           | 0.7856      | 0.8519       | 0.8156     |69| 0.6254        | 12.0  | 528  | 0.6419          | 0.9325    | 0.8730    | 0.8209     | 0.8462   | 0.8036    | 0.2201           | 0.8492      | 0.8222       | 0.8327     |70| 0.6254        | 13.0  | 572  | 0.6979          | 0.9258    | 0.9048    | 0.7808     | 0.8382   | 0.7940    | 0.2184           | 0.8772      | 0.8137       | 0.8426     |71| 0.6254        | 14.0  | 616  | 0.6541          | 0.9292    | 0.8492    | 0.8231     | 0.8359   | 0.7909    | 0.2209           | 0.7926      | 0.8504       | 0.8174     |72| 0.6254        | 15.0  | 660  | 0.6407          | 0.9342    | 0.8333    | 0.8537     | 0.8434   | 0.8019    | 0.2146           | 0.8340      | 0.8351       | 0.8298     |73| 0.6254        | 16.0  | 704  | 0.6448          | 0.9342    | 0.8016    | 0.8783     | 0.8382   | 0.7983    | 0.2171           | 0.8149      | 0.8424       | 0.8225     |74| 0.6254        | 17.0  | 748  | 0.6556          | 0.9309    | 0.7619    | 0.8972     | 0.8240   | 0.7854    | 0.2196           | 0.8181      | 0.8375       | 0.8218     |75| 0.6254        | 18.0  | 792  | 0.6642          | 0.9275    | 0.8571    | 0.8120     | 0.8340   | 0.7881    | 0.2163           | 0.8244      | 0.8389       | 0.8292     |76| 0.6254        | 19.0  | 836  | 0.6546          | 0.9376    | 0.8254    | 0.8739     | 0.8490   | 0.8102    | 0.2226           | 0.8066      | 0.8405       | 0.8203     |77| 0.6254        | 20.0  | 880  | 0.6580          | 0.9292    | 0.8413    | 0.8281     | 0.8346   | 0.7896    | 0.2192           | 0.8123      | 0.8417       | 0.8242     |78 79 80### Framework versions81 82- Transformers 4.49.083- Pytorch 2.6.0+cu12484- Datasets 3.3.285- Tokenizers 0.21.086