lora-roberta-large-fine-emo

anniew666/lora-roberta-large-fine-emo

lora-roberta-large-fine-emo is a machine learning model from anniew666. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

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At a glance

Library: peft
License: mit
Access: Public
Created: Aug 17, 2023
Updated: Aug 31, 2023
SHA: 1a7a0849

Base models

Model card

From the Hugging Face model README

lora-roberta-large-fine-emo

This model is a fine-tuned version of roberta-large on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.7876
Accuracy: 0.7175
Prec: 0.6298
Recall: 0.5922
F1: 0.6045
B Acc: 0.5922
Prec Joy: 0.6497
Recall Joy: 0.7540
F1 Joy: 0.6980
Prec Anger: 0.6146
Recall Anger: 0.6435
F1 Anger: 0.6287
Prec Disgust: 0.4805
Recall Disgust: 0.4393
F1 Disgust: 0.4590
Prec Fear: 0.6954
Recall Fear: 0.5953
F1 Fear: 0.6415
Prec Neutral: 0.8410
Recall Neutral: 0.8250
F1 Neutral: 0.8329
Prec Sadness: 0.6719
Recall Sadness: 0.6124
F1 Sadness: 0.6408
Prec Surprise: 0.5377
Recall Surprise: 0.4215
F1 Surprise: 0.4726
Prec Amusement: 0.7297
Recall Amusement: 0.8284
F1 Amusement: 0.7759
Prec Anxiety: 0.4420
Recall Anxiety: 0.4896
F1 Anxiety: 0.4646
Prec Guilt: 0.7911
Recall Guilt: 0.7740
F1 Guilt: 0.7824
Prec Love: 0.6545
Recall Love: 0.5996
F1 Love: 0.6259
Prec Optimism: 0.7228
Recall Optimism: 0.5915
F1 Optimism: 0.6506
Prec Pessimism: 0.3571
Recall Pessimism: 0.125
F1 Pessimism: 0.1852

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: 128
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.05
num_epochs: 20.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Prec	Recall	F1	B Acc	Prec Joy	Recall Joy	F1 Joy	Prec Anger	Recall Anger	F1 Anger	Prec Disgust	Recall Disgust	F1 Disgust	Prec Fear	Recall Fear	F1 Fear	Prec Neutral	Recall Neutral	F1 Neutral	Prec Sadness	Recall Sadness	F1 Sadness	Prec Surprise	Recall Surprise	F1 Surprise	Prec Amusement	Recall Amusement	F1 Amusement	Prec Anxiety	Recall Anxiety	F1 Anxiety	Prec Guilt	Recall Guilt	F1 Guilt	Prec Love	Recall Love	F1 Love	Prec Optimism	Recall Optimism	F1 Optimism	Prec Pessimism	Recall Pessimism	F1 Pessimism
1.0157	1.0	1756	0.9691	0.6663	0.5337	0.5038	0.5122	0.5038	0.6173	0.6805	0.6474	0.5681	0.4796	0.5201	0.4619	0.3893	0.4225	0.6567	0.4117	0.5061	0.8134	0.8269	0.8201	0.5633	0.56	0.5616	0.4613	0.3204	0.3782	0.6554	0.7657	0.7062	0.3637	0.5292	0.4311	0.7048	0.6130	0.6557	0.4626	0.5186	0.4890	0.6092	0.4538	0.5202	0.0	0.0	0.0
0.9186	2.0	3512	0.8979	0.6873	0.5497	0.5388	0.5376	0.5388	0.6239	0.7230	0.6698	0.5644	0.5817	0.5729	0.4373	0.4357	0.4365	0.5923	0.5743	0.5831	0.8235	0.8298	0.8266	0.6103	0.5373	0.5715	0.5451	0.2796	0.3696	0.5699	0.8746	0.6901	0.4437	0.4174	0.4302	0.7510	0.6872	0.7177	0.5687	0.5129	0.5393	0.6165	0.5509	0.5818	0.0	0.0	0.0
0.8686	3.0	5268	0.8550	0.6993	0.5880	0.5603	0.5700	0.5603	0.6758	0.6879	0.6818	0.5462	0.6339	0.5868	0.4386	0.4339	0.4363	0.6578	0.5485	0.5982	0.8159	0.8431	0.8293	0.6360	0.5707	0.6015	0.4874	0.3753	0.4241	0.6702	0.8251	0.7396	0.4647	0.4431	0.4537	0.8147	0.6600	0.7293	0.5840	0.5634	0.5735	0.6426	0.5994	0.6202	0.2105	0.1	0.1356
0.8386	4.0	7024	0.8276	0.7080	0.6131	0.5607	0.5805	0.5607	0.6812	0.6885	0.6848	0.6102	0.5716	0.5903	0.4691	0.4339	0.4508	0.6514	0.5813	0.6143	0.7868	0.8752	0.8286	0.6617	0.5702	0.6126	0.5489	0.3441	0.4230	0.7143	0.8251	0.7657	0.4824	0.4481	0.4646	0.7817	0.7251	0.7523	0.6292	0.5500	0.5870	0.6866	0.5759	0.6264	0.2667	0.1	0.1455
0.8125	5.0	8780	0.8200	0.7102	0.6011	0.5845	0.5887	0.5845	0.6745	0.7044	0.6891	0.6341	0.5779	0.6047	0.4914	0.4071	0.4453	0.7038	0.5836	0.6381	0.8196	0.8475	0.8333	0.6499	0.5858	0.6162	0.4950	0.4237	0.4565	0.6650	0.8845	0.7592	0.4218	0.5361	0.4721	0.7771	0.7251	0.7502	0.6509	0.5777	0.6121	0.6140	0.6197	0.6168	0.2174	0.125	0.1587
0.7981	6.0	10536	0.8111	0.7131	0.5989	0.5719	0.5793	0.5719	0.6839	0.6987	0.6912	0.6277	0.6090	0.6182	0.5151	0.3964	0.4480	0.6894	0.6023	0.6429	0.8023	0.8626	0.8313	0.7311	0.5231	0.6098	0.5577	0.3688	0.4440	0.6710	0.8548	0.7518	0.4138	0.5697	0.4794	0.8109	0.7288	0.7676	0.5881	0.6301	0.6084	0.6943	0.5900	0.6379	0.0	0.0	0.0
0.7883	7.0	12292	0.8049	0.7133	0.6065	0.5998	0.6008	0.5998	0.6620	0.7362	0.6971	0.6193	0.6080	0.6136	0.4283	0.4911	0.4576	0.6456	0.6199	0.6325	0.8404	0.8292	0.8348	0.6721	0.5849	0.6255	0.5047	0.4075	0.4509	0.7096	0.8548	0.7754	0.4352	0.5114	0.4702	0.7722	0.7541	0.7630	0.6345	0.6072	0.6206	0.7111	0.5931	0.6468	0.25	0.2	0.2222
0.7724	8.0	14048	0.7981	0.7174	0.6296	0.5832	0.5941	0.5832	0.6869	0.7086	0.6976	0.6292	0.6277	0.6284	0.5897	0.3696	0.4544	0.6136	0.6538	0.6331	0.8224	0.8514	0.8367	0.6859	0.5716	0.6235	0.5257	0.4075	0.4591	0.7333	0.7987	0.7646	0.4078	0.5618	0.4725	0.7782	0.7740	0.7761	0.6324	0.6101	0.6211	0.7046	0.5712	0.6309	0.375	0.075	0.1250
0.7644	9.0	15804	0.7984	0.7155	0.6223	0.5727	0.5888	0.5727	0.6514	0.7481	0.6964	0.6069	0.6473	0.6265	0.5131	0.4196	0.4617	0.6629	0.6234	0.6426	0.8348	0.8311	0.8329	0.6112	0.6533	0.6316	0.5514	0.3806	0.4504	0.7335	0.8086	0.7692	0.4865	0.3749	0.4235	0.8020	0.7396	0.7695	0.6567	0.5891	0.6211	0.7298	0.5790	0.6457	0.25	0.05	0.0833
0.7531	10.0	17560	0.7929	0.7181	0.6020	0.5761	0.5853	0.5761	0.6524	0.7454	0.6958	0.6170	0.6291	0.6230	0.5325	0.3804	0.4437	0.6675	0.6222	0.6441	0.8269	0.8428	0.8348	0.6892	0.5924	0.6372	0.5144	0.4215	0.4634	0.6939	0.8680	0.7713	0.4655	0.4402	0.4525	0.7802	0.7703	0.7753	0.6405	0.6149	0.6274	0.7464	0.5618	0.6411	0.0	0.0	0.0
0.7462	11.0	19316	0.7868	0.7187	0.6001	0.5776	0.5861	0.5776	0.6634	0.7412	0.7001	0.6197	0.6425	0.6309	0.4802	0.4125	0.4438	0.6403	0.6246	0.6323	0.8266	0.8413	0.8339	0.6714	0.6067	0.6374	0.5649	0.3978	0.4669	0.7096	0.8548	0.7754	0.4643	0.4688	0.4665	0.7973	0.7468	0.7712	0.6703	0.5815	0.6228	0.6930	0.5900	0.6374	0.0	0.0	0.0
0.7357	12.0	21072	0.7876	0.7175	0.6298	0.5922	0.6045	0.5922	0.6497	0.7540	0.6980	0.6146	0.6435	0.6287	0.4805	0.4393	0.4590	0.6954	0.5953	0.6415	0.8410	0.8250	0.8329	0.6719	0.6124	0.6408	0.5377	0.4215	0.4726	0.7297	0.8284	0.7759	0.4420	0.4896	0.4646	0.7911	0.7740	0.7824	0.6545	0.5996	0.6259	0.7228	0.5915	0.6506	0.3571	0.125	0.1852
0.7242	13.0	22828	0.7810	0.7205	0.6004	0.5846	0.5903	0.5846	0.6679	0.7310	0.6980	0.6422	0.6277	0.6348	0.4782	0.4304	0.4530	0.6712	0.6304	0.6502	0.8237	0.8440	0.8337	0.6598	0.6231	0.6409	0.5565	0.4022	0.4669	0.7213	0.8713	0.7892	0.4847	0.4243	0.4525	0.7698	0.7740	0.7719	0.6276	0.6330	0.6303	0.7022	0.6088	0.6521	0.0	0.0	0.0
0.7216	14.0	24584	0.7839	0.7200	0.6543	0.5946	0.6044	0.5946	0.6680	0.7423	0.7032	0.5927	0.6814	0.6340	0.5271	0.4	0.4548	0.7023	0.6070	0.6512	0.8409	0.8267	0.8337	0.6973	0.5907	0.6396	0.5560	0.4108	0.4725	0.7330	0.8515	0.7878	0.4193	0.5707	0.4835	0.7890	0.7776	0.7832	0.6516	0.6044	0.6271	0.7283	0.5915	0.6528	0.6	0.075	0.1333
0.7136	15.0	26340	0.7812	0.7228	0.6390	0.5889	0.6012	0.5889	0.6691	0.7383	0.7020	0.6679	0.5898	0.6265	0.5154	0.4482	0.4795	0.6839	0.6175	0.6490	0.8221	0.8489	0.8353	0.6613	0.6213	0.6407	0.5508	0.4140	0.4727	0.7260	0.8482	0.7823	0.4718	0.4718	0.4718	0.7932	0.7631	0.7779	0.6205	0.6454	0.6327	0.7254	0.5994	0.6564	0.4	0.05	0.0889
0.7092	16.0	28096	0.7793	0.7225	0.6047	0.5858	0.5928	0.5858	0.6690	0.7391	0.7023	0.6432	0.6296	0.6363	0.5098	0.4179	0.4593	0.6622	0.6398	0.6508	0.8315	0.8426	0.8370	0.6647	0.616	0.6394	0.5688	0.4	0.4697	0.7301	0.8482	0.7847	0.4468	0.4896	0.4672	0.7833	0.7649	0.7740	0.6341	0.6177	0.6258	0.7182	0.6103	0.6599	0.0	0.0	0.0
0.7052	17.0	29852	0.7800	0.7224	0.6070	0.5875	0.5949	0.5875	0.6625	0.7469	0.7021	0.6365	0.6344	0.6355	0.5312	0.4107	0.4632	0.6874	0.6199	0.6519	0.8338	0.8367	0.8353	0.6665	0.62	0.6424	0.5529	0.4161	0.4748	0.7270	0.8614	0.7885	0.4559	0.4906	0.4726	0.7996	0.7649	0.7819	0.6444	0.6168	0.6303	0.6935	0.6197	0.6545	0.0	0.0	0.0
0.6988	18.0	31608	0.7770	0.7233	0.6089	0.5873	0.5950	0.5873	0.6674	0.7446	0.7038	0.6192	0.6483	0.6334	0.5072	0.4393	0.4708	0.6937	0.6199	0.6547	0.8287	0.8427	0.8356	0.6801	0.6084	0.6423	0.5853	0.3946	0.4714	0.7216	0.8812	0.7935	0.4646	0.4738	0.4691	0.7885	0.7685	0.7784	0.6457	0.6063	0.6254	0.7132	0.6072	0.6560	0.0	0.0	0.0
0.7021	19.0	33364	0.7778	0.7238	0.6356	0.5900	0.6000	0.5900	0.6731	0.7389	0.7045	0.6348	0.6306	0.6327	0.5010	0.4482	0.4731	0.6972	0.6222	0.6576	0.8285	0.8431	0.8358	0.6651	0.6249	0.6444	0.5852	0.3989	0.4744	0.7421	0.8548	0.7945	0.4534	0.4817	0.4671	0.7896	0.7667	0.7780	0.6365	0.6311	0.6338	0.7228	0.6041	0.6581	0.3333	0.025	0.0465
0.703	20.0	35120	0.7772	0.7230	0.6333	0.5894	0.5987	0.5894	0.6716	0.7385	0.7035	0.6341	0.6310	0.6326	0.5083	0.4375	0.4702	0.6816	0.6234	0.6512	0.8272	0.8432	0.8351	0.6761	0.6133	0.6432	0.5690	0.4032	0.4720	0.7358	0.8548	0.7908	0.4536	0.4886	0.4705	0.7860	0.7703	0.7781	0.6407	0.6273	0.6339	0.7153	0.6056	0.6559	0.3333	0.025	0.0465

Framework versions

Transformers 4.32.0.dev0
Pytorch 2.0.1
Datasets 2.12.0
Tokenizers 0.11.0

Library: peft
License: mit
Created: Aug 17, 2023
Updated: Aug 31, 2023