README.md

metadata

base_model: Anwaarma/Merged-Server-praj
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: S04-PC
    results: []

S04-PC

This model is a fine-tuned version of Anwaarma/Merged-Server-praj on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.5103
• Accuracy: 0.68
• F1: 0.8095

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: 5e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• 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
No log	0.01	50	0.6565	0.61	0.6017
No log	0.01	100	0.6527	0.66	0.6604
No log	0.02	150	0.6491	0.63	0.6306
No log	0.03	200	0.6530	0.65	0.6488
No log	0.03	250	0.6844	0.66	0.6605
No log	0.04	300	0.6677	0.67	0.6705
No log	0.04	350	0.6830	0.65	0.6505
No log	0.05	400	0.6547	0.63	0.6297
No log	0.06	450	0.6579	0.63	0.6306
0.6131	0.06	500	0.6316	0.62	0.62
0.6131	0.07	550	0.6677	0.65	0.6505
0.6131	0.08	600	0.6725	0.68	0.6804
0.6131	0.08	650	0.6304	0.66	0.6600
0.6131	0.09	700	0.6332	0.67	0.6705
0.6131	0.09	750	0.5832	0.68	0.6804
0.6131	0.1	800	0.5870	0.68	0.6794
0.6131	0.11	850	0.5742	0.7	0.6994
0.6131	0.11	900	0.5861	0.68	0.6794
0.6131	0.12	950	0.5922	0.68	0.6794
0.5945	0.13	1000	0.5769	0.67	0.6697
0.5945	0.13	1050	0.6237	0.7	0.7004
0.5945	0.14	1100	0.6270	0.69	0.6897
0.5945	0.14	1150	0.6026	0.65	0.6497
0.5945	0.15	1200	0.6483	0.69	0.6902
0.5945	0.16	1250	0.6043	0.65	0.6502
0.5945	0.16	1300	0.5933	0.69	0.6897
0.5945	0.17	1350	0.5837	0.69	0.6902
0.5945	0.18	1400	0.6172	0.68	0.6784
0.5945	0.18	1450	0.5930	0.69	0.6902
0.5822	0.19	1500	0.5816	0.69	0.6902
0.5822	0.19	1550	0.5893	0.69	0.6902
0.5822	0.2	1600	0.5926	0.69	0.6905
0.5822	0.21	1650	0.5815	0.67	0.6705
0.5822	0.21	1700	0.6059	0.67	0.6689
0.5822	0.22	1750	0.5986	0.68	0.6794

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu121
• Datasets 2.16.0
• Tokenizers 0.15.0