copilot_relex_v1_with_context

This model is a fine-tuned version of microsoft/deberta-v3-small on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0299
• Accuracy: 0.0075
• F1: 0.0127
• Precision: 0.0064
• Recall: 0.8358
• Learning Rate: 0.0

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: 2e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Rate
No log	1.0	26	0.5156	0.0531	0.0154	0.0078	0.9701	0.0000
No log	2.0	52	0.3270	0.0077	0.0152	0.0077	1.0	0.0000
No log	3.0	78	0.1951	0.0077	0.0152	0.0077	1.0	0.0000
No log	4.0	104	0.1153	0.0077	0.0152	0.0077	1.0	0.0000
No log	5.0	130	0.0759	0.0077	0.0152	0.0077	1.0	0.0000
No log	6.0	156	0.0584	0.0077	0.0152	0.0077	1.0	0.0000
No log	7.0	182	0.0503	0.0077	0.0152	0.0077	1.0	0.0000
No log	8.0	208	0.0462	0.0077	0.0152	0.0077	1.0	0.0000
No log	9.0	234	0.0440	0.0077	0.0152	0.0077	1.0	0.0000
No log	10.0	260	0.0427	0.0077	0.0152	0.0077	1.0	0.0000
No log	11.0	286	0.0419	0.0077	0.0152	0.0077	1.0	0.0000
No log	12.0	312	0.0413	0.0077	0.0152	0.0077	1.0	0.0000
No log	13.0	338	0.0410	0.0077	0.0152	0.0077	1.0	0.0000
No log	14.0	364	0.0407	0.0077	0.0152	0.0077	1.0	0.0000
No log	15.0	390	0.0405	0.0077	0.0152	0.0077	1.0	0.0000
No log	16.0	416	0.0403	0.0077	0.0152	0.0077	1.0	0.0000
No log	17.0	442	0.0402	0.0077	0.0152	0.0077	1.0	0.0000
No log	18.0	468	0.0400	0.0077	0.0152	0.0077	1.0	0.0000
No log	19.0	494	0.0399	0.0077	0.0152	0.0077	1.0	0.0000
0.1144	20.0	520	0.0397	0.0077	0.0152	0.0077	1.0	0.0000
0.1144	21.0	546	0.0388	0.0077	0.0152	0.0077	1.0	0.0000
0.1144	22.0	572	0.0388	0.0077	0.0152	0.0077	1.0	0.0000
0.1144	23.0	598	0.0387	0.0077	0.0152	0.0077	1.0	0.0000
0.1144	24.0	624	0.0375	0.0077	0.0152	0.0077	1.0	0.0000
0.1144	25.0	650	0.0376	0.0077	0.0152	0.0077	1.0	0.0000
0.1144	26.0	676	0.0369	0.0077	0.0152	0.0077	1.0	0.0000
0.1144	27.0	702	0.0367	0.0077	0.0152	0.0077	1.0	0.0000
0.1144	28.0	728	0.0373	0.0077	0.0152	0.0077	1.0	0.0000
0.1144	29.0	754	0.0362	0.0077	0.0152	0.0077	1.0	0.0000
0.1144	30.0	780	0.0361	0.0077	0.0152	0.0077	1.0	0.0000
0.1144	31.0	806	0.0358	0.0077	0.0152	0.0077	1.0	0.0000
0.1144	32.0	832	0.0355	0.0077	0.0152	0.0077	1.0	0.0000
0.1144	33.0	858	0.0329	0.0073	0.0145	0.0073	0.9552	0.0000
0.1144	34.0	884	0.0327	0.0078	0.0152	0.0077	1.0	0.0000
0.1144	35.0	910	0.0328	0.0074	0.0147	0.0074	0.9701	0.0000
0.1144	36.0	936	0.0324	0.0075	0.0147	0.0074	0.9701	0.0000
0.1144	37.0	962	0.0316	0.0075	0.0147	0.0074	0.9701	0.0000
0.1144	38.0	988	0.0326	0.0075	0.0145	0.0073	0.9552	0.0000
0.029	39.0	1014	0.0312	0.0074	0.0145	0.0073	0.9552	0.0000
0.029	40.0	1040	0.0313	0.0072	0.0141	0.0071	0.9254	0.0000
0.029	41.0	1066	0.0320	0.0073	0.0143	0.0072	0.9403	0.0000
0.029	42.0	1092	0.0316	0.0074	0.0145	0.0073	0.9552	0.0000
0.029	43.0	1118	0.0310	0.0072	0.0136	0.0069	0.8955	0.0000
0.029	44.0	1144	0.0311	0.0072	0.0141	0.0071	0.9254	0.0000
0.029	45.0	1170	0.0310	0.0072	0.0127	0.0064	0.8358	0.0000
0.029	46.0	1196	0.0312	0.0071	0.0134	0.0067	0.8806	0.0000
0.029	47.0	1222	0.0308	0.0071	0.0134	0.0067	0.8806	0.0000
0.029	48.0	1248	0.0312	0.0072	0.0136	0.0069	0.8955	0.0000
0.029	49.0	1274	0.0309	0.0073	0.0136	0.0069	0.8955	0.0000
0.029	50.0	1300	0.0307	0.0070	0.0129	0.0065	0.8507	1e-05
0.029	51.0	1326	0.0303	0.0071	0.0134	0.0067	0.8806	0.0000
0.029	52.0	1352	0.0307	0.0073	0.0134	0.0067	0.8806	0.0000
0.029	53.0	1378	0.0309	0.0073	0.0134	0.0067	0.8806	0.0000
0.029	54.0	1404	0.0312	0.0072	0.0136	0.0069	0.8955	0.0000
0.029	55.0	1430	0.0303	0.0073	0.0136	0.0069	0.8955	9e-06
0.029	56.0	1456	0.0300	0.0071	0.0132	0.0066	0.8657	0.0000
0.029	57.0	1482	0.0301	0.0069	0.0125	0.0063	0.8209	0.0000
0.0205	58.0	1508	0.0302	0.0072	0.0132	0.0066	0.8657	0.0000
0.0205	59.0	1534	0.0303	0.0071	0.0129	0.0065	0.8507	0.0000
0.0205	60.0	1560	0.0308	0.0073	0.0132	0.0066	0.8657	0.0000
0.0205	61.0	1586	0.0309	0.0074	0.0136	0.0069	0.8955	0.0000
0.0205	62.0	1612	0.0306	0.0078	0.0130	0.0065	0.8507	0.0000
0.0205	63.0	1638	0.0308	0.0077	0.0130	0.0065	0.8507	0.0000
0.0205	64.0	1664	0.0303	0.0071	0.0127	0.0064	0.8358	0.0000
0.0205	65.0	1690	0.0312	0.0077	0.0132	0.0066	0.8657	7e-06
0.0205	66.0	1716	0.0304	0.0073	0.0132	0.0066	0.8657	0.0000
0.0205	67.0	1742	0.0305	0.0073	0.0132	0.0066	0.8657	0.0000
0.0205	68.0	1768	0.0304	0.0074	0.0132	0.0066	0.8657	0.0000
0.0205	69.0	1794	0.0306	0.0072	0.0129	0.0065	0.8507	0.0000
0.0205	70.0	1820	0.0314	0.0080	0.0134	0.0068	0.8806	6e-06
0.0205	71.0	1846	0.0314	0.0075	0.0132	0.0066	0.8657	0.0000
0.0205	72.0	1872	0.0307	0.0075	0.0132	0.0066	0.8657	0.0000
0.0205	73.0	1898	0.0300	0.0075	0.0127	0.0064	0.8358	0.0000
0.0205	74.0	1924	0.0301	0.0072	0.0127	0.0064	0.8358	0.0000
0.0205	75.0	1950	0.0297	0.0075	0.0132	0.0066	0.8657	5e-06
0.0205	76.0	1976	0.0306	0.0075	0.0130	0.0065	0.8507	0.0000
0.016	77.0	2002	0.0299	0.0073	0.0125	0.0063	0.8209	0.0000
0.016	78.0	2028	0.0301	0.0074	0.0125	0.0063	0.8209	0.0000
0.016	79.0	2054	0.0301	0.0078	0.0127	0.0064	0.8358	0.0000
0.016	80.0	2080	0.0306	0.0078	0.0130	0.0065	0.8507	0.0000
0.016	81.0	2106	0.0302	0.0073	0.0125	0.0063	0.8209	0.0000
0.016	82.0	2132	0.0305	0.0073	0.0129	0.0065	0.8507	0.0000
0.016	83.0	2158	0.0303	0.0073	0.0127	0.0064	0.8358	0.0000
0.016	84.0	2184	0.0302	0.0072	0.0129	0.0065	0.8507	0.0000
0.016	85.0	2210	0.0302	0.0072	0.0127	0.0064	0.8358	3e-06
0.016	86.0	2236	0.0299	0.0072	0.0125	0.0063	0.8209	0.0000
0.016	87.0	2262	0.0296	0.0069	0.0125	0.0063	0.8209	0.0000
0.016	88.0	2288	0.0299	0.0073	0.0127	0.0064	0.8358	0.0000
0.016	89.0	2314	0.0297	0.0072	0.0125	0.0063	0.8209	0.0000
0.016	90.0	2340	0.0296	0.0073	0.0125	0.0063	0.8209	0.0000
0.016	91.0	2366	0.0299	0.0071	0.0125	0.0063	0.8209	0.0000
0.016	92.0	2392	0.0293	0.0071	0.0125	0.0063	0.8209	0.0000
0.016	93.0	2418	0.0301	0.0073	0.0127	0.0064	0.8358	0.0000
0.016	94.0	2444	0.0294	0.0071	0.0125	0.0063	0.8209	0.0000
0.016	95.0	2470	0.0296	0.0072	0.0125	0.0063	0.8209	0.0000
0.016	96.0	2496	0.0298	0.0074	0.0125	0.0063	0.8209	0.0000
0.0136	97.0	2522	0.0299	0.0073	0.0127	0.0064	0.8358	0.0000
0.0136	98.0	2548	0.0298	0.0074	0.0125	0.0063	0.8209	0.0000
0.0136	99.0	2574	0.0299	0.0075	0.0127	0.0064	0.8358	0.0000
0.0136	100.0	2600	0.0299	0.0075	0.0127	0.0064	0.8358	0.0

Framework versions

• Transformers 4.40.1
• Pytorch 2.2.1+cu121
• Datasets 2.19.0
• Tokenizers 0.19.1