cc933add989680f2866fa401c563cfe0

This model is a fine-tuned version of distilbert/distilbert-base-cased-distilled-squad on the contemmcm/amazon_reviews_2013 [cell-phone] dataset. It achieves the following results on the evaluation set:

• Loss: 1.0403
• Data Size: 1.0
• Epoch Runtime: 56.9385
• Accuracy: 0.6692
• F1 Macro: 0.5932

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: 8
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• total_train_batch_size: 32
• total_eval_batch_size: 32
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: constant
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Data Size	Epoch Runtime	Accuracy	F1 Macro
No log	0	0	1.6302	0	4.7704	0.1732	0.0964
No log	1	1973	1.4307	0.0078	5.7951	0.3843	0.1670
0.0304	2	3946	1.1702	0.0156	5.6756	0.5273	0.3048
1.0749	3	5919	1.0693	0.0312	6.4148	0.5619	0.3888
0.9284	4	7892	0.9144	0.0625	8.2780	0.6183	0.4840
0.8648	5	9865	0.8611	0.125	11.6165	0.6374	0.5563
0.8067	6	11838	0.8124	0.25	18.4281	0.6611	0.5660
0.8162	7	13811	0.8069	0.5	31.4892	0.6617	0.6024
0.7219	8.0	15784	0.8267	1.0	59.2021	0.6616	0.5953
0.6043	9.0	17757	0.8239	1.0	58.2451	0.6641	0.6039
0.4667	10.0	19730	0.8673	1.0	57.8605	0.6655	0.6096
0.3702	11.0	21703	1.0403	1.0	56.9385	0.6692	0.5932

Framework versions

• Transformers 4.57.0
• Pytorch 2.8.0+cu128
• Datasets 4.2.0
• Tokenizers 0.22.1