metadata

tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: >-
      distilrubert-tiny-cased-conversational-v1_single_finetuned_on_cedr_augmented
    results: []

distilrubert-tiny-cased-conversational-v1_single_finetuned_on_cedr_augmented

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: 0.5908
Accuracy: 0.8653
F1: 0.8656
Precision: 0.8665
Recall: 0.8653

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
0.9172	1.0	69	0.5124	0.8246	0.8220	0.8271	0.8246
0.4709	2.0	138	0.4279	0.8528	0.8505	0.8588	0.8528
0.3194	3.0	207	0.3770	0.8737	0.8727	0.8740	0.8737
0.2459	4.0	276	0.3951	0.8685	0.8682	0.8692	0.8685
0.1824	5.0	345	0.4005	0.8831	0.8834	0.8841	0.8831
0.1515	6.0	414	0.4356	0.8800	0.8797	0.8801	0.8800
0.1274	7.0	483	0.4642	0.8727	0.8726	0.8731	0.8727
0.0833	8.0	552	0.5226	0.8633	0.8627	0.8631	0.8633
0.073	9.0	621	0.5327	0.8695	0.8686	0.8692	0.8695
0.0575	10.0	690	0.5908	0.8653	0.8656	0.8665	0.8653

Framework versions

Transformers 4.19.3
Pytorch 1.11.0+cu113
Datasets 2.2.2
Tokenizers 0.12.1