qwen2_Magiccoder_evol_10k_reverse

This model is a fine-tuned version of Qwen/Qwen2-7B on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.8272

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: 0.0001
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 32
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 0.02
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
0.8303	0.0261	4	0.8571
0.8267	0.0522	8	0.8449
0.8201	0.0784	12	0.8389
0.8002	0.1045	16	0.8436
0.8491	0.1306	20	0.8414
0.7448	0.1567	24	0.8434
0.7606	0.1828	28	0.8459
0.9214	0.2089	32	0.8474
0.8071	0.2351	36	0.8466
0.8353	0.2612	40	0.8479
0.8762	0.2873	44	0.8473
0.8544	0.3134	48	0.8475
0.7855	0.3395	52	0.8482
0.7725	0.3656	56	0.8467
0.8044	0.3918	60	0.8470
0.8282	0.4179	64	0.8446
0.853	0.4440	68	0.8449
0.8047	0.4701	72	0.8439
0.8145	0.4962	76	0.8431
0.8063	0.5223	80	0.8411
0.8782	0.5485	84	0.8395
0.7944	0.5746	88	0.8395
0.8728	0.6007	92	0.8370
0.7882	0.6268	96	0.8363
0.8999	0.6529	100	0.8354
0.7857	0.6790	104	0.8341
0.8258	0.7052	108	0.8331
0.7877	0.7313	112	0.8317
0.7686	0.7574	116	0.8305
0.7422	0.7835	120	0.8299
0.8229	0.8096	124	0.8292
0.7577	0.8357	128	0.8285
0.8811	0.8619	132	0.8278
0.8243	0.8880	136	0.8277
0.8243	0.9141	140	0.8275
0.8096	0.9402	144	0.8275
0.8476	0.9663	148	0.8274
0.8154	0.9925	152	0.8272

Framework versions

• PEFT 0.7.1
• Transformers 4.40.2
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1