metadata

tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: >-
      distilrubert-tiny-cased-conversational-v1_single_finetuned_empathy_classifier
    results: []

distilrubert-tiny-cased-conversational-v1_single_finetuned_empathy_classifier

This model is a fine-tuned version of DeepPavlov/distilrubert-tiny-cased-conversational-v1 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.0183
Accuracy: 0.6218
F1: 0.6262
Precision: 0.6318
Recall: 0.6218

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: 0.0001
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
1.0456	1.0	9	0.9718	0.4958	0.4197	0.6526	0.4958
0.9042	2.0	18	0.8920	0.5882	0.5769	0.5784	0.5882
0.7923	3.0	27	0.8427	0.6134	0.5861	0.5935	0.6134
0.7544	4.0	36	0.8400	0.6387	0.6234	0.6344	0.6387
0.6675	5.0	45	0.8410	0.6303	0.6095	0.6184	0.6303
0.6091	6.0	54	0.9095	0.6050	0.6041	0.6396	0.6050
0.6279	7.0	63	0.8596	0.6723	0.6692	0.6725	0.6723
0.4968	8.0	72	0.8725	0.6303	0.6274	0.6253	0.6303
0.4459	9.0	81	0.9120	0.6387	0.6395	0.6426	0.6387
0.4122	10.0	90	0.9478	0.6303	0.6262	0.6248	0.6303
0.3244	11.0	99	0.9746	0.6387	0.6375	0.6381	0.6387
0.3535	12.0	108	1.0183	0.6218	0.6262	0.6318	0.6218

Framework versions

Transformers 4.20.1
Pytorch 1.12.0+cu113
Datasets 2.4.0
Tokenizers 0.12.1