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contemmcm/
e984c0a18b4bb0b3129fc01967cc11e8

Name: e984c0a18b4bb0b3129fc01967cc11e8
Rating: 2.5 (5 reviews)

generated_from_trainer

deepseek-ai/DeepSeek-R1-Distill-Qwen-7B

finetune

mit

text-embeddings-inference

endpoints_compatible

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e984c0a18b4bb0b3129fc01967cc11e8

This model is a fine-tuned version of deepseek-ai/DeepSeek-R1-Distill-Qwen-7B on the nyu-mll/glue [sst2] dataset. It achieves the following results on the evaluation set:

Loss: 3.6548
Data Size: 1.0
Epoch Runtime: 1682.1848
Accuracy: 0.8484
F1 Macro: 0.8479
Rouge1: 0.8484
Rouge2: 0.0
Rougel: 0.8484
Rougelsum: 0.8484

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	Rouge1	Rougel	Rougelsum
No log	0	0	4.4033	0	3.2051	0.4676	0.4285	0.4676	0.4676	0.4664
No log	1	2104	3.5203	0.0078	16.0487	0.4861	0.3291	0.4861	0.4861	0.4873
No log	2	4208	4.0656	0.0156	32.5313	0.5093	0.3374	0.5093	0.5093	0.5081
0.0762	3	6312	1.8766	0.0312	68.3174	0.7743	0.7743	0.7743	0.7743	0.7731
1.6694	4	8416	1.5764	0.0625	118.3939	0.8380	0.8372	0.8380	0.8380	0.8380
1.3589	5	10520	1.4074	0.125	230.0990	0.8414	0.8406	0.8414	0.8414	0.8414
1.0252	6	12624	1.3402	0.25	437.4193	0.8704	0.8701	0.8704	0.8704	0.8704
0.8041	7	14728	1.2264	0.5	856.1002	0.875	0.8750	0.875	0.875	0.875
0.6276	8.0	16832	1.5403	1.0	1702.3318	0.8542	0.8532	0.8530	0.8542	0.8542
0.5738	9.0	18936	2.3254	1.0	1693.5311	0.8461	0.8457	0.8449	0.8461	0.8461
0.7041	10.0	21040	2.1962	1.0	1689.3121	0.8461	0.8458	0.8461	0.8461	0.8461
0.3462	11.0	23144	3.6548	1.0	1682.1848	0.8484	0.8479	0.8484	0.8484	0.8484

Framework versions

Transformers 4.57.0
Pytorch 2.8.0+cu128
Datasets 4.0.0
Tokenizers 0.22.1

contemmcm/e984c0a18b4bb0b3129fc01967cc11e8

e984c0a18b4bb0b3129fc01967cc11e8

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

contemmcm/
e984c0a18b4bb0b3129fc01967cc11e8