metadata

library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: d_bert_v1
    results: []

d_bert_v1

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3069
Accuracy: 0.8929
F1: 0.8931
Precision: 0.8942
Recall: 0.8929

Model description

Discriminator model for semantically similar classes

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: 2e-05
train_batch_size: 32
eval_batch_size: 128
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.5
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
1.5322	0.16	500	1.1796	0.6822	0.6712	0.6833	0.6822
0.7762	0.32	1000	0.5988	0.8002	0.7985	0.7973	0.8002
0.5433	0.48	1500	0.4945	0.8290	0.8288	0.8295	0.8290
0.4879	0.64	2000	0.4819	0.8301	0.8319	0.8407	0.8301
0.4447	0.8	2500	0.4223	0.8496	0.8511	0.8542	0.8496
0.4187	0.96	3000	0.4062	0.8525	0.8541	0.8594	0.8525
0.3746	1.12	3500	0.3892	0.8657	0.8650	0.8654	0.8657
0.3615	1.28	4000	0.3829	0.8637	0.8656	0.8694	0.8637
0.3507	1.44	4500	0.3501	0.8735	0.8748	0.8784	0.8735
0.3369	1.6	5000	0.3900	0.8567	0.8601	0.8759	0.8567
0.332	1.76	5500	0.3247	0.8842	0.8850	0.8867	0.8842
0.3316	1.92	6000	0.3280	0.8807	0.8803	0.8816	0.8807
0.2858	2.08	6500	0.3257	0.8881	0.8879	0.8881	0.8881
0.2613	2.24	7000	0.3282	0.8850	0.8861	0.8889	0.8850
0.2575	2.4	7500	0.3209	0.8875	0.8881	0.8913	0.8875
0.241	2.56	8000	0.3204	0.8896	0.8905	0.8930	0.8896
0.2431	2.7200	8500	0.3225	0.8851	0.8862	0.8903	0.8851
0.2248	2.88	9000	0.3069	0.8929	0.8931	0.8942	0.8929

Framework versions

Transformers 4.44.2
Pytorch 2.4.0
Datasets 3.0.0
Tokenizers 0.19.1