bert-base-uncased_Climate_LRTC

This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.9664
• Accuracy: 0.2968
• Macro Precision: 0.2213
• Macro F1: 0.2191

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 12

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Macro Precision	Macro F1
No log	1.0	54	2.0709	0.2831	0.1087	0.0798
No log	2.0	108	2.0722	0.1781	0.1404	0.0862
No log	3.0	162	1.9856	0.2785	0.2237	0.1878
No log	4.0	216	1.9580	0.3242	0.2526	0.2262
No log	5.0	270	1.9310	0.2420	0.2384	0.2106
No log	6.0	324	1.9647	0.2192	0.2233	0.1840
No log	7.0	378	1.9454	0.2831	0.2603	0.2234
No log	8.0	432	1.9512	0.2694	0.2258	0.2154
No log	9.0	486	1.9467	0.2603	0.2161	0.2081
1.5695	10.0	540	1.9493	0.2831	0.2327	0.2261
1.5695	11.0	594	1.9629	0.3059	0.2408	0.2334
1.5695	12.0	648	1.9664	0.2968	0.2213	0.2191

Framework versions

• Transformers 5.0.0
• Pytorch 2.10.0+cu128
• Datasets 4.0.0
• Tokenizers 0.22.2