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contemmcm/
8f01cd7a39361a8ab6275aa87dff535c

Name: 8f01cd7a39361a8ab6275aa87dff535c
Rating: 2.5 (7 reviews)

generated_from_trainer

Qwen/Qwen2.5-1.5B

finetune

apache-2.0

text-embeddings-inference

endpoints_compatible

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8f01cd7a39361a8ab6275aa87dff535c

This model is a fine-tuned version of Qwen/Qwen2.5-1.5B on the dair-ai/emotion [split] dataset. It achieves the following results on the evaluation set:

Loss: 1.1777
Data Size: 1.0
Epoch Runtime: 112.9324
Accuracy: 0.9309
F1 Macro: 0.8917

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	25.7280	0	5.5925	0.0801	0.0328
No log	1	500	7.2399	0.0078	5.6067	0.3352	0.1892
No log	2	1000	6.8457	0.0156	8.3054	0.3674	0.1269
No log	3	1500	4.4181	0.0312	11.9044	0.6431	0.5092
No log	4	2000	3.2759	0.0625	17.1476	0.7818	0.7234
0.2177	5	2500	1.9468	0.125	24.8466	0.8861	0.8400
1.2022	6	3000	1.2000	0.25	39.8889	0.8952	0.7783
0.1416	7	3500	0.7323	0.5	65.2222	0.9269	0.8823
0.7848	8.0	4000	0.6269	1.0	117.4305	0.9325	0.8845
0.4878	9.0	4500	0.7784	1.0	111.0526	0.9274	0.8870
0.4853	10.0	5000	0.8550	1.0	112.8829	0.9294	0.8904
0.3548	11.0	5500	0.8772	1.0	113.3440	0.9304	0.8856
0.4829	12.0	6000	1.1777	1.0	112.9324	0.9309	0.8917

Framework versions

Transformers 4.57.0
Pytorch 2.8.0+cu128
Datasets 4.3.0
Tokenizers 0.22.1

contemmcm/8f01cd7a39361a8ab6275aa87dff535c

8f01cd7a39361a8ab6275aa87dff535c

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

contemmcm/
8f01cd7a39361a8ab6275aa87dff535c