lbl-file2-fold0

This model is a fine-tuned version of shreyashvora/lbl-file1-fold3 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.2090
• Accuracy: 0.6212
• F1: 0.5802
• Precision: 0.6232
• Recall: 0.6212
• Accuracy Label Label 0: 0.0
• Accuracy Label Label 1: 0.0
• Accuracy Label Label 2: 0.0
• Accuracy Label Label 3: 0.0
• Accuracy Label Label 4: 0.0
• Accuracy Label Label 5: 0.1161
• Accuracy Label Label 6: 0.2898
• Accuracy Label Label 7: 0.6071
• Accuracy Label Label 8: 0.0
• Accuracy Label Label 9: 0.9123

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: 2e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Accuracy Label Label 0	Accuracy Label Label 1	Accuracy Label Label 2	Accuracy Label Label 3	Accuracy Label Label 4	Accuracy Label Label 5	Accuracy Label Label 6	Accuracy Label Label 7	Accuracy Label Label 8	Accuracy Label Label 9
No log	0.12	125	1.3072	0.5860	0.5406	0.6242	0.5860	0.0	0.0	0.0	0.0	0.0	0.1196	0.1966	0.5138	0.0	0.9460
No log	0.24	250	1.2671	0.5988	0.5552	0.6246	0.5988	0.0	0.0	0.0	0.0	0.0	0.1196	0.2199	0.5469	0.0	0.9366
No log	0.36	375	1.2643	0.6193	0.5750	0.6205	0.6193	0.0	0.0	0.0	0.0	0.0	0.1473	0.1771	0.6248	0.0	0.9026
No log	0.48	500	1.1849	0.6266	0.5855	0.6159	0.6266	0.0	0.0	0.0	0.0	0.0	0.2010	0.2293	0.6358	0.0	0.8947
No log	0.6	625	1.2457	0.6037	0.5567	0.6277	0.6037	0.0	0.0	0.0	0.0	0.0	0.1092	0.1491	0.5715	0.0	0.9334
No log	0.73	750	1.2090	0.6212	0.5802	0.6232	0.6212	0.0	0.0	0.0	0.0	0.0	0.1161	0.2898	0.6071	0.0	0.9123
No log	0.85	875	1.2322	0.6082	0.5662	0.6264	0.6082	0.0	0.0	0.0	0.0	0.0	0.1334	0.2572	0.5631	0.0	0.9346
0.7405	0.97	1000	1.2014	0.6258	0.5844	0.6243	0.6258	0.0	0.0	0.0	0.0	0.0	0.1369	0.2693	0.6187	0.0	0.9125

Framework versions

• Transformers 4.30.2
• Pytorch 2.5.1+cu124
• Datasets 3.2.0
• Tokenizers 0.13.3