TED_CLM_gpt2_tedlium_bigger_lr – AI Model by Lakoc | AlphaNeural AI

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Lakoc/
TED_CLM_gpt2_tedlium_bigger_lr

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text-generation

generated_from_trainer

autotrain_compatible

text-generation-inference

endpoints_compatible

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TED_CLM_gpt2_tedlium_bigger_lr

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

Loss: 1.8755
Accuracy: 0.5540

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: 0.004
train_batch_size: 128
eval_batch_size: 128
seed: 42
distributed_type: multi-GPU
num_devices: 4
total_train_batch_size: 512
total_eval_batch_size: 512
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 20000
num_epochs: 15.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.0351	0.62	3000	2.2280	0.4798
1.9186	1.24	6000	2.0994	0.5074
1.88	1.86	9000	2.0577	0.5142
1.8505	2.49	12000	2.0113	0.5223
1.8284	3.11	15000	1.9957	0.5279
1.8182	3.73	18000	1.9891	0.5305
1.8061	4.35	21000	1.9617	0.5371
1.7969	4.97	24000	1.9413	0.5369
2.0383	5.59	27000	2.1697	0.4894
1.7668	6.22	30000	1.9366	0.5397
1.7556	6.84	33000	1.9303	0.5402
1.7492	7.46	36000	1.9140	0.5432
1.7409	8.08	39000	1.9088	0.5445
1.7317	8.7	42000	1.9030	0.5455
1.7218	9.32	45000	1.9040	0.5496
1.7261	9.94	48000	1.8952	0.5506
1.7175	10.57	51000	1.8959	0.5498
1.708	11.19	54000	1.8909	0.5510
1.7056	11.81	57000	1.8917	0.5518
1.6971	12.43	60000	1.8879	0.5523
1.6986	13.05	63000	1.8790	0.5532
1.6972	13.67	66000	1.8799	0.5526
1.6858	14.29	69000	1.8782	0.5543
1.6875	14.92	72000	1.8755	0.5540

Framework versions

Transformers 4.31.0.dev0
Pytorch 2.1.0+cu121
Datasets 2.13.1
Tokenizers 0.13.3