README.md

metadata

tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: electra-large-discriminator-nli-efl-hateval
    results: []

electra-large-discriminator-nli-efl-hateval

This model is a fine-tuned version of ynie/electra-large-discriminator-snli_mnli_fever_anli_R1_R2_R3-nli on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.4166
• Accuracy: 0.798
• F1: 0.7968

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: 1e-06
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.4175	1.0	210	0.4020	0.7317	0.7305
0.3061	2.0	420	0.3520	0.768	0.7675
0.2588	3.0	630	0.3253	0.79	0.7888
0.234	4.0	840	0.3373	0.788	0.7877
0.2116	5.0	1050	0.3247	0.804	0.8033
0.1974	6.0	1260	0.3400	0.793	0.7928
0.1807	7.0	1470	0.3511	0.7973	0.7969
0.1715	8.0	1680	0.3496	0.7993	0.7989
0.1577	9.0	1890	0.3507	0.8043	0.8032
0.1469	10.0	2100	0.3604	0.798	0.7970
0.1394	11.0	2310	0.3734	0.7967	0.7957
0.1322	12.0	2520	0.3929	0.7913	0.7906
0.1231	13.0	2730	0.3954	0.795	0.7941
0.1189	14.0	2940	0.3994	0.7977	0.7963
0.1143	15.0	3150	0.3995	0.7993	0.7980
0.1083	16.0	3360	0.4125	0.7927	0.7918
0.1079	17.0	3570	0.4036	0.7993	0.7979
0.1055	18.0	3780	0.4121	0.7967	0.7956
0.1006	19.0	3990	0.4152	0.7973	0.7961
0.101	20.0	4200	0.4166	0.798	0.7968

Framework versions

• Transformers 4.17.0
• Pytorch 1.11.0+cu113
• Datasets 2.0.0
• Tokenizers 0.11.6