Arabic_FineTuningAraBERT_AugV4-trial2_k1_task1_organization_fold0

This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.8043
• Qwk: 0.7268
• Mse: 0.8043
• Rmse: 0.8968

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.0667	2	5.3857	0.0	5.3857	2.3207
No log	0.1333	4	3.2299	0.0027	3.2299	1.7972
No log	0.2	6	1.7033	0.1778	1.7033	1.3051
No log	0.2667	8	1.2584	0.2159	1.2584	1.1218
No log	0.3333	10	1.2060	0.0742	1.2060	1.0982
No log	0.4	12	1.3288	0.4854	1.3288	1.1528
No log	0.4667	14	1.4327	0.3259	1.4327	1.1970
No log	0.5333	16	1.5300	0.2184	1.5300	1.2369
No log	0.6	18	1.5359	0.2435	1.5359	1.2393
No log	0.6667	20	1.3307	0.3226	1.3307	1.1536
No log	0.7333	22	1.1492	0.4830	1.1492	1.0720
No log	0.8	24	0.8873	0.5106	0.8873	0.9420
No log	0.8667	26	0.9113	0.3364	0.9113	0.9546
No log	0.9333	28	0.8242	0.5323	0.8242	0.9078
No log	1.0	30	1.1596	0.3831	1.1596	1.0768
No log	1.0667	32	1.3726	0.3816	1.3726	1.1716
No log	1.1333	34	1.4508	0.3226	1.4508	1.2045
No log	1.2	36	1.4111	0.3816	1.4111	1.1879
No log	1.2667	38	1.1806	0.3831	1.1806	1.0865
No log	1.3333	40	0.9499	0.5312	0.9499	0.9746
No log	1.4	42	0.8107	0.5304	0.8107	0.9004
No log	1.4667	44	0.6970	0.6075	0.6970	0.8348
No log	1.5333	46	0.7168	0.5674	0.7168	0.8467
No log	1.6	48	0.7132	0.5674	0.7132	0.8445
No log	1.6667	50	0.7372	0.5674	0.7372	0.8586
No log	1.7333	52	0.6976	0.5263	0.6976	0.8352
No log	1.8	54	0.7046	0.5413	0.7046	0.8394
No log	1.8667	56	0.7251	0.5545	0.7251	0.8515
No log	1.9333	58	0.7257	0.5811	0.7257	0.8519
No log	2.0	60	0.8599	0.7042	0.8599	0.9273
No log	2.0667	62	1.0463	0.5742	1.0463	1.0229
No log	2.1333	64	0.9787	0.6564	0.9787	0.9893
No log	2.2	66	0.8863	0.6503	0.8863	0.9414
No log	2.2667	68	0.8468	0.7123	0.8468	0.9202
No log	2.3333	70	0.7648	0.5723	0.7648	0.8745
No log	2.4	72	0.6991	0.5633	0.6991	0.8361
No log	2.4667	74	0.7304	0.5633	0.7304	0.8546
No log	2.5333	76	0.9507	0.7525	0.9507	0.9751
No log	2.6	78	1.1681	0.7221	1.1681	1.0808
No log	2.6667	80	1.1511	0.6127	1.1511	1.0729
No log	2.7333	82	0.9790	0.6776	0.9790	0.9894
No log	2.8	84	0.6980	0.7008	0.6980	0.8355
No log	2.8667	86	0.5887	0.6165	0.5887	0.7673
No log	2.9333	88	0.6506	0.6355	0.6506	0.8066
No log	3.0	90	0.5959	0.6355	0.5959	0.7719
No log	3.0667	92	0.5404	0.6719	0.5404	0.7351
No log	3.1333	94	0.7248	0.7986	0.7248	0.8514
No log	3.2	96	1.0280	0.6776	1.0280	1.0139
No log	3.2667	98	1.2998	0.6119	1.2998	1.1401
No log	3.3333	100	1.2866	0.6119	1.2866	1.1343
No log	3.4	102	1.0527	0.6550	1.0527	1.0260
No log	3.4667	104	0.7864	0.7627	0.7864	0.8868
No log	3.5333	106	0.6154	0.7439	0.6154	0.7845
No log	3.6	108	0.5424	0.7618	0.5424	0.7365
No log	3.6667	110	0.5244	0.7533	0.5244	0.7241
No log	3.7333	112	0.5468	0.7533	0.5468	0.7395
No log	3.8	114	0.6163	0.7355	0.6163	0.7851
No log	3.8667	116	0.6544	0.7439	0.6544	0.8089
No log	3.9333	118	0.6669	0.7439	0.6669	0.8166
No log	4.0	120	0.6427	0.7367	0.6427	0.8017
No log	4.0667	122	0.7210	0.7704	0.7210	0.8491
No log	4.1333	124	0.7779	0.7986	0.7779	0.8820
No log	4.2	126	0.7765	0.8168	0.7765	0.8812
No log	4.2667	128	0.7463	0.8168	0.7463	0.8639
No log	4.3333	130	0.6790	0.7439	0.6790	0.8240
No log	4.4	132	0.6092	0.7204	0.6092	0.7805
No log	4.4667	134	0.6065	0.7181	0.6065	0.7788
No log	4.5333	136	0.6599	0.7439	0.6599	0.8123
No log	4.6	138	0.7979	0.8098	0.7979	0.8933
No log	4.6667	140	0.8938	0.8098	0.8938	0.9454
No log	4.7333	142	0.8511	0.8098	0.8511	0.9225
No log	4.8	144	0.7067	0.7529	0.7067	0.8407
No log	4.8667	146	0.5945	0.7355	0.5945	0.7711
No log	4.9333	148	0.5649	0.7008	0.5649	0.7516
No log	5.0	150	0.5981	0.7355	0.5981	0.7733
No log	5.0667	152	0.6656	0.7529	0.6656	0.8159
No log	5.1333	154	0.7173	0.7529	0.7173	0.8469
No log	5.2	156	0.7542	0.7801	0.7542	0.8684
No log	5.2667	158	0.7518	0.7801	0.7518	0.8671
No log	5.3333	160	0.8161	0.7346	0.8161	0.9034
No log	5.4	162	0.8351	0.7779	0.8351	0.9139
No log	5.4667	164	0.7792	0.7779	0.7792	0.8827
No log	5.5333	166	0.7254	0.7196	0.7254	0.8517
No log	5.6	168	0.6935	0.7382	0.6935	0.8328
No log	5.6667	170	0.6844	0.7599	0.6844	0.8273
No log	5.7333	172	0.7231	0.7689	0.7231	0.8503
No log	5.8	174	0.7996	0.7525	0.7996	0.8942
No log	5.8667	176	0.8551	0.7616	0.8551	0.9247
No log	5.9333	178	0.8262	0.7616	0.8262	0.9090
No log	6.0	180	0.7452	0.8098	0.7452	0.8633
No log	6.0667	182	0.6525	0.7529	0.6525	0.8078
No log	6.1333	184	0.6447	0.7529	0.6447	0.8029
No log	6.2	186	0.6647	0.7529	0.6647	0.8153
No log	6.2667	188	0.7182	0.7529	0.7182	0.8474
No log	6.3333	190	0.8144	0.7937	0.8144	0.9024
No log	6.4	192	0.8856	0.7937	0.8856	0.9411
No log	6.4667	194	0.9341	0.7937	0.9341	0.9665
No log	6.5333	196	0.9351	0.7612	0.9351	0.9670
No log	6.6	198	0.8674	0.7979	0.8674	0.9313
No log	6.6667	200	0.8485	0.7979	0.8485	0.9211
No log	6.7333	202	0.8596	0.7979	0.8596	0.9272
No log	6.8	204	0.8493	0.7979	0.8493	0.9216
No log	6.8667	206	0.8583	0.7979	0.8583	0.9265
No log	6.9333	208	0.8988	0.7979	0.8988	0.9481
No log	7.0	210	0.8918	0.7979	0.8918	0.9444
No log	7.0667	212	0.8785	0.7430	0.8785	0.9373
No log	7.1333	214	0.8492	0.7144	0.8492	0.9215
No log	7.2	216	0.7861	0.7144	0.7861	0.8866
No log	7.2667	218	0.7437	0.6997	0.7437	0.8624
No log	7.3333	220	0.7548	0.6997	0.7548	0.8688
No log	7.4	222	0.7754	0.7268	0.7754	0.8806
No log	7.4667	224	0.7531	0.7268	0.7531	0.8678
No log	7.5333	226	0.7676	0.7268	0.7676	0.8761
No log	7.6	228	0.8205	0.7268	0.8205	0.9058
No log	7.6667	230	0.8726	0.7346	0.8726	0.9341
No log	7.7333	232	0.8584	0.7346	0.8584	0.9265
No log	7.8	234	0.8172	0.7346	0.8172	0.9040
No log	7.8667	236	0.8080	0.7268	0.8080	0.8989
No log	7.9333	238	0.8049	0.7268	0.8049	0.8972
No log	8.0	240	0.8290	0.7268	0.8290	0.9105
No log	8.0667	242	0.8446	0.7268	0.8446	0.9190
No log	8.1333	244	0.8433	0.7268	0.8433	0.9183
No log	8.2	246	0.8181	0.7268	0.8181	0.9045
No log	8.2667	248	0.8030	0.7268	0.8030	0.8961
No log	8.3333	250	0.7975	0.7268	0.7975	0.8930
No log	8.4	252	0.8155	0.6997	0.8155	0.9030
No log	8.4667	254	0.8388	0.7068	0.8388	0.9159
No log	8.5333	256	0.8509	0.7068	0.8509	0.9225
No log	8.6	258	0.8361	0.7068	0.8361	0.9144
No log	8.6667	260	0.8024	0.6997	0.8024	0.8958
No log	8.7333	262	0.7665	0.6997	0.7665	0.8755
No log	8.8	264	0.7415	0.6932	0.7415	0.8611
No log	8.8667	266	0.7288	0.6932	0.7288	0.8537
No log	8.9333	268	0.7342	0.6932	0.7342	0.8568
No log	9.0	270	0.7290	0.6932	0.7290	0.8538
No log	9.0667	272	0.7358	0.6932	0.7358	0.8578
No log	9.1333	274	0.7405	0.7196	0.7405	0.8605
No log	9.2	276	0.7587	0.7196	0.7587	0.8711
No log	9.2667	278	0.7844	0.7196	0.7844	0.8856
No log	9.3333	280	0.8017	0.7268	0.8017	0.8954
No log	9.4	282	0.8107	0.7268	0.8107	0.9004
No log	9.4667	284	0.8114	0.7268	0.8114	0.9008
No log	9.5333	286	0.8111	0.7268	0.8111	0.9006
No log	9.6	288	0.8117	0.7268	0.8117	0.9009
No log	9.6667	290	0.8142	0.7346	0.8142	0.9023
No log	9.7333	292	0.8104	0.7268	0.8104	0.9002
No log	9.8	294	0.8107	0.7268	0.8107	0.9004
No log	9.8667	296	0.8083	0.7268	0.8083	0.8991
No log	9.9333	298	0.8059	0.7268	0.8059	0.8977
No log	10.0	300	0.8043	0.7268	0.8043	0.8968

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.0+cu118
• Datasets 2.21.0
• Tokenizers 0.19.1