gpt2-larger-walser – AI Model by dh-unibe | AlphaNeural AI

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dh-unibe/
gpt2-larger-walser

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text-generation

generated_from_trainer

autotrain_compatible

text-generation-inference

endpoints_compatible

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22_09_07_walser_blocks_larger_fp16_5ep

This model is a fine-tuned version of stefan-it/german-gpt2-larger on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 4.1738
Accuracy: 0.2760

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
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.45	50	5.2435	0.1883
No log	0.91	100	4.6670	0.2259
No log	1.36	150	4.4367	0.2481
No log	1.82	200	4.3258	0.2597
6.175	2.27	250	4.2705	0.2648
6.175	2.73	300	4.2318	0.2697
6.175	3.18	350	4.2090	0.2719
6.175	3.64	400	4.1915	0.2740
6.175	4.09	450	4.1823	0.2746
3.9191	4.55	500	4.1761	0.2757
3.9191	5.0	550	4.1738	0.2760

Framework versions

Transformers 4.22.0.dev0
Pytorch 1.11.0.post202
Datasets 2.3.2
Tokenizers 0.12.1