tiny-llama-lora-new

This model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-Chat-v1.0 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.2252
Accuracy: 0.8203
Precision: 0.8184
Recall: 0.8203
Precision Macro: 0.7732
Recall Macro: 0.7380
Macro Fpr: 0.0162
Weighted Fpr: 0.0154
Weighted Specificity: 0.9743
Macro Specificity: 0.9863
Weighted Sensitivity: 0.8203
Macro Sensitivity: 0.7380
F1 Micro: 0.8203
F1 Macro: 0.7435
F1 Weighted: 0.8173

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: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	Precision Macro	Recall Macro	Macro Fpr	Weighted Fpr	Weighted Specificity	Macro Specificity	Weighted Sensitivity	Macro Sensitivity	F1 Micro	F1 Macro	F1 Weighted
No log	1.0	160	0.6615	0.8002	0.8040	0.8002	0.7266	0.6678	0.0182	0.0175	0.9726	0.9848	0.8002	0.6678	0.8002	0.6790	0.7959
No log	2.0	321	0.6996	0.8064	0.8110	0.8064	0.7448	0.7207	0.0177	0.0169	0.9737	0.9853	0.8064	0.7207	0.8064	0.7235	0.8039
No log	3.0	482	0.8202	0.8125	0.8119	0.8125	0.7577	0.7080	0.0171	0.0162	0.9711	0.9856	0.8125	0.7080	0.8125	0.7180	0.8085
0.2932	4.0	643	0.9493	0.8141	0.8204	0.8141	0.7593	0.7327	0.0166	0.0160	0.9744	0.9859	0.8141	0.7327	0.8141	0.7415	0.8154
0.2932	5.0	803	1.0610	0.8110	0.8110	0.8110	0.7596	0.7427	0.0172	0.0164	0.9738	0.9857	0.8110	0.7427	0.8110	0.7413	0.8087
0.2932	6.0	964	1.1362	0.8149	0.8160	0.8149	0.7731	0.7380	0.0167	0.0160	0.9741	0.9859	0.8149	0.7380	0.8149	0.7408	0.8128
0.0107	7.0	1125	1.1713	0.8102	0.8123	0.8102	0.7734	0.7310	0.0171	0.0165	0.9736	0.9856	0.8102	0.7310	0.8102	0.7343	0.8085
0.0107	8.0	1286	1.1786	0.8156	0.8141	0.8156	0.7656	0.7349	0.0166	0.0159	0.9740	0.9860	0.8156	0.7349	0.8156	0.7374	0.8128
0.0107	9.0	1446	1.1960	0.8187	0.8170	0.8187	0.7693	0.7368	0.0163	0.0156	0.9743	0.9862	0.8187	0.7368	0.8187	0.7400	0.8157
0.0016	10.0	1607	1.2049	0.8156	0.8150	0.8156	0.7659	0.7353	0.0166	0.0159	0.9741	0.9860	0.8156	0.7353	0.8156	0.7376	0.8131
0.0016	11.0	1768	1.2137	0.8156	0.8147	0.8156	0.7661	0.7353	0.0166	0.0159	0.9741	0.9860	0.8156	0.7353	0.8156	0.7377	0.8130
0.0016	12.0	1929	1.2158	0.8156	0.8145	0.8156	0.7664	0.7353	0.0166	0.0159	0.9739	0.9860	0.8156	0.7353	0.8156	0.7379	0.8129
0.0011	13.0	2089	1.2202	0.8187	0.8169	0.8187	0.7720	0.7372	0.0163	0.0156	0.9741	0.9862	0.8187	0.7372	0.8187	0.7425	0.8158
0.0011	14.0	2250	1.2229	0.8187	0.8169	0.8187	0.7720	0.7372	0.0163	0.0156	0.9741	0.9862	0.8187	0.7372	0.8187	0.7425	0.8158
0.0011	14.93	2400	1.2252	0.8203	0.8184	0.8203	0.7732	0.7380	0.0162	0.0154	0.9743	0.9863	0.8203	0.7380	0.8203	0.7435	0.8173

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.19.0
Tokenizers 0.15.1

xshubhamx
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tiny-llama-lora-new

tiny-llama-lora-new

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Model tree for xshubhamx/tiny-llama-lora-new

Evaluation results