chickens-60-epoch-200-images-aug

This model is a fine-tuned version of facebook/detr-resnet-50 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.3172
• Map: 0.7813
• Map 50: 0.9672
• Map 75: 0.9061
• Map Small: 0.5029
• Map Medium: 0.7534
• Map Large: 0.8581
• Mar 1: 0.2609
• Mar 10: 0.8237
• Mar 100: 0.8407
• Mar Small: 0.5407
• Mar Medium: 0.8181
• Mar Large: 0.9033
• Map Chicken: 0.7893
• Mar 100 Chicken: 0.8558
• Map Duck: 0.7616
• Mar 100 Duck: 0.825
• Map Plant: 0.7929
• Mar 100 Plant: 0.8414

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: 1e-05
• train_batch_size: 2
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• num_epochs: 60

Training results

Training Loss	Epoch	Step	Validation Loss	Map	Map 50	Map 75	Map Small	Map Medium	Map Large	Mar 1	Mar 10	Mar 100	Mar Small	Mar Medium	Mar Large	Map Chicken	Mar 100 Chicken	Map Duck	Mar 100 Duck	Map Plant	Mar 100 Plant
1.39	1.0	497	1.4568	0.1658	0.2544	0.19	0.0007	0.1178	0.572	0.0735	0.2448	0.2951	0.0444	0.2733	0.7627	0.0281	0.15	0.0297	0.0324	0.4395	0.7029
1.0818	2.0	994	1.2408	0.1924	0.2866	0.2221	0.0107	0.1379	0.6468	0.0738	0.2559	0.2789	0.0333	0.2522	0.75	0.038	0.1558	0.0	0.0	0.5391	0.6809
1.0382	3.0	1491	1.1565	0.2389	0.3456	0.2667	0.0175	0.2088	0.6989	0.0965	0.3342	0.3793	0.3111	0.3535	0.7928	0.094	0.4112	0.0	0.0	0.6229	0.7266
0.9389	4.0	1988	1.0233	0.2651	0.3695	0.3088	0.0187	0.2392	0.7309	0.104	0.3987	0.46	0.3519	0.4331	0.8088	0.137	0.6396	0.0	0.0	0.6583	0.7404
0.8606	5.0	2485	0.9402	0.3365	0.502	0.3846	0.0152	0.3165	0.7061	0.1389	0.4708	0.5159	0.1667	0.494	0.7807	0.2694	0.6954	0.0976	0.1345	0.6424	0.7178
0.8217	6.0	2982	0.8550	0.3399	0.497	0.3807	0.0512	0.3161	0.7385	0.1247	0.4612	0.4907	0.1222	0.4637	0.8108	0.304	0.6796	0.0474	0.0554	0.6685	0.7371
0.8555	7.0	3479	0.7985	0.3644	0.512	0.4361	0.0648	0.3433	0.7396	0.1417	0.5009	0.531	0.2296	0.5061	0.801	0.3468	0.7642	0.0697	0.0926	0.6768	0.7363
0.7846	8.0	3976	0.7775	0.4093	0.5643	0.4936	0.0811	0.3834	0.7663	0.1702	0.541	0.5874	0.2926	0.563	0.8176	0.3666	0.7942	0.1645	0.2162	0.6968	0.752
1.1121	9.0	4473	0.7245	0.3964	0.5446	0.4803	0.0597	0.3762	0.759	0.1392	0.5093	0.5425	0.2889	0.5193	0.8111	0.4271	0.8033	0.0679	0.0764	0.6942	0.7479
0.7181	10.0	4970	0.7218	0.3985	0.5517	0.4777	0.1619	0.3747	0.7474	0.14	0.5086	0.5403	0.2852	0.5159	0.8033	0.4358	0.785	0.0785	0.0959	0.6812	0.74
0.7338	11.0	5467	0.7031	0.5215	0.7323	0.6247	0.2342	0.4985	0.7549	0.1927	0.6175	0.6458	0.3667	0.6213	0.8124	0.5003	0.7454	0.3735	0.4466	0.6908	0.7455
0.7107	12.0	5964	0.6559	0.4871	0.6743	0.5933	0.1353	0.4609	0.7674	0.1755	0.5688	0.5983	0.3222	0.5742	0.8131	0.5366	0.7946	0.227	0.2514	0.6979	0.7488
0.6867	13.0	6461	0.6307	0.5689	0.7843	0.6921	0.2219	0.5409	0.7784	0.204	0.6467	0.6719	0.2407	0.6486	0.8265	0.5677	0.775	0.4308	0.4804	0.7081	0.7602
0.6659	14.0	6958	0.6498	0.5874	0.834	0.7233	0.1414	0.564	0.7351	0.2123	0.6699	0.6914	0.337	0.6663	0.8023	0.5821	0.7738	0.5066	0.5655	0.6736	0.7348
0.6979	15.0	7455	0.5984	0.6138	0.874	0.7383	0.1613	0.5832	0.7824	0.2239	0.6946	0.7171	0.2963	0.6913	0.8278	0.5625	0.7554	0.5718	0.6405	0.7071	0.7553
0.5107	16.0	7952	0.5714	0.6356	0.9011	0.7713	0.2066	0.6084	0.789	0.2249	0.72	0.7417	0.3704	0.7177	0.8415	0.5761	0.7579	0.6135	0.6953	0.7172	0.7719
0.6271	17.0	8449	0.5257	0.6636	0.9051	0.7937	0.351	0.6331	0.8044	0.2317	0.7393	0.7635	0.4556	0.7407	0.85	0.6165	0.7917	0.6398	0.7122	0.7346	0.7867
0.5645	18.0	8946	0.5132	0.6835	0.9215	0.8205	0.4803	0.6611	0.792	0.2429	0.7496	0.769	0.5185	0.7498	0.8382	0.6527	0.7871	0.6679	0.7372	0.7299	0.7826
0.6116	19.0	9443	0.5127	0.6574	0.9452	0.7874	0.4883	0.6233	0.7941	0.2285	0.7226	0.7382	0.5111	0.7106	0.8435	0.6334	0.7325	0.62	0.7095	0.7188	0.7727
0.5896	20.0	9940	0.4924	0.6682	0.9411	0.8196	0.5009	0.6364	0.7906	0.2348	0.732	0.747	0.5222	0.7187	0.8438	0.6419	0.7417	0.6441	0.7284	0.7186	0.7709
0.538	21.0	10437	0.4794	0.6745	0.947	0.8269	0.4886	0.6421	0.7972	0.2385	0.7357	0.7528	0.5222	0.7256	0.8536	0.6632	0.7508	0.6336	0.723	0.7266	0.7846
0.581	22.0	10934	0.4552	0.6926	0.9556	0.8348	0.5355	0.662	0.8043	0.2412	0.7491	0.7662	0.5556	0.7429	0.8569	0.6813	0.7629	0.6591	0.7405	0.7374	0.7951
0.4655	23.0	11431	0.4418	0.6984	0.9577	0.8555	0.506	0.6693	0.799	0.2408	0.7511	0.7678	0.5481	0.7446	0.849	0.7097	0.7825	0.6537	0.7345	0.7317	0.7865
0.4435	24.0	11928	0.4251	0.7043	0.9552	0.8358	0.3469	0.6769	0.802	0.2439	0.7612	0.7763	0.3889	0.7496	0.8614	0.7102	0.7892	0.6703	0.7507	0.7325	0.7891
0.521	25.0	12425	0.4064	0.7268	0.962	0.8799	0.3649	0.6998	0.8139	0.25	0.7767	0.7937	0.6222	0.7714	0.8657	0.7058	0.78	0.7239	0.7939	0.7507	0.807
0.5358	26.0	12922	0.4021	0.7158	0.9596	0.8604	0.3895	0.6886	0.8158	0.2497	0.7677	0.7857	0.4148	0.7646	0.866	0.7198	0.8012	0.6743	0.7493	0.7533	0.8066
0.478	27.0	13419	0.4045	0.712	0.9597	0.8763	0.4779	0.6811	0.8136	0.2431	0.7606	0.7788	0.5037	0.7558	0.8611	0.6946	0.7763	0.6954	0.7615	0.746	0.7986
0.4684	28.0	13916	0.3945	0.7246	0.9589	0.8756	0.3809	0.6987	0.8248	0.2436	0.7704	0.7887	0.4481	0.7704	0.868	0.7186	0.7837	0.6913	0.7682	0.7639	0.8141
0.4758	29.0	14413	0.3802	0.7363	0.9607	0.8843	0.4282	0.7047	0.8264	0.2492	0.7806	0.7994	0.5	0.7777	0.8765	0.7271	0.8	0.7199	0.7811	0.762	0.817
0.5724	30.0	14910	0.3773	0.7508	0.9608	0.8825	0.4597	0.7246	0.8255	0.2525	0.7929	0.8103	0.5741	0.787	0.8755	0.7633	0.8275	0.7277	0.7905	0.7612	0.8129
0.5229	31.0	15407	0.3797	0.7341	0.964	0.8791	0.4828	0.705	0.8393	0.2508	0.7812	0.7987	0.5111	0.773	0.8843	0.7341	0.8037	0.7007	0.7757	0.7675	0.8166
0.4247	32.0	15904	0.3720	0.7533	0.9598	0.8998	0.4806	0.7271	0.8303	0.2523	0.7979	0.8164	0.5185	0.7945	0.8758	0.7561	0.8271	0.7396	0.8061	0.7641	0.816
0.4791	33.0	16401	0.3666	0.7556	0.968	0.8978	0.4072	0.725	0.8319	0.2561	0.7978	0.8154	0.4778	0.7944	0.8804	0.7659	0.8292	0.7335	0.7953	0.7676	0.8219
0.4107	34.0	16898	0.3568	0.751	0.9592	0.8941	0.5087	0.722	0.8416	0.2537	0.7945	0.8128	0.5667	0.7901	0.8886	0.7645	0.8263	0.7143	0.7851	0.7742	0.8271
0.5572	35.0	17395	0.3460	0.7607	0.9613	0.9006	0.4575	0.7377	0.838	0.259	0.8017	0.82	0.5111	0.8016	0.8817	0.7648	0.8304	0.7384	0.8	0.779	0.8295
0.4188	36.0	17892	0.3547	0.7522	0.9623	0.8907	0.4372	0.7274	0.8258	0.2572	0.7951	0.8122	0.4852	0.7921	0.8729	0.7627	0.8288	0.7286	0.7919	0.7653	0.816
0.3833	37.0	18389	0.3474	0.7589	0.9619	0.9009	0.484	0.731	0.8389	0.2569	0.8028	0.8208	0.5296	0.799	0.8876	0.7742	0.8404	0.7286	0.7939	0.7739	0.8281
0.4402	38.0	18886	0.3546	0.7577	0.9662	0.9037	0.4664	0.73	0.8281	0.2579	0.7997	0.8166	0.5074	0.7943	0.8791	0.7628	0.8238	0.7449	0.8088	0.7654	0.8174
0.4705	39.0	19383	0.3458	0.7676	0.9625	0.8974	0.556	0.7396	0.8375	0.2606	0.8096	0.8269	0.6111	0.8058	0.884	0.7782	0.8413	0.7503	0.8142	0.7743	0.8254
0.4476	40.0	19880	0.3528	0.7613	0.9603	0.8951	0.4661	0.7346	0.8308	0.2579	0.8062	0.8248	0.5111	0.8027	0.8827	0.7736	0.8408	0.7424	0.8122	0.768	0.8215
0.4515	41.0	20377	0.3540	0.7652	0.9646	0.8982	0.5283	0.7364	0.8366	0.257	0.8087	0.8274	0.5926	0.8047	0.8899	0.7645	0.8296	0.7573	0.8216	0.7738	0.8309
0.5283	42.0	20874	0.3416	0.761	0.964	0.8967	0.4546	0.7305	0.8388	0.2547	0.8077	0.8256	0.5407	0.8031	0.8895	0.7714	0.8379	0.7368	0.8088	0.7748	0.8301
0.4371	43.0	21371	0.3397	0.7609	0.9658	0.9026	0.4562	0.7316	0.8418	0.2555	0.8073	0.8254	0.5185	0.8032	0.8905	0.7686	0.8388	0.736	0.8074	0.778	0.8299
0.3756	44.0	21868	0.3444	0.7645	0.9615	0.9075	0.5114	0.735	0.8403	0.2607	0.8085	0.8255	0.5815	0.8011	0.8925	0.7749	0.8379	0.744	0.8101	0.7746	0.8283
0.4228	45.0	22365	0.3341	0.7744	0.9645	0.8991	0.5075	0.7461	0.8398	0.2617	0.8159	0.8332	0.5593	0.8117	0.8899	0.7876	0.8479	0.7597	0.8216	0.776	0.8301
0.3976	46.0	22862	0.3294	0.7751	0.9648	0.907	0.4606	0.7469	0.8427	0.2638	0.8171	0.8352	0.5222	0.8156	0.8915	0.7821	0.8487	0.761	0.8223	0.7821	0.8346
0.4371	47.0	23359	0.3312	0.7744	0.9665	0.9009	0.4494	0.7465	0.8476	0.2596	0.8157	0.8334	0.5148	0.8127	0.8938	0.783	0.8471	0.7565	0.8182	0.7838	0.8348
0.3589	48.0	23856	0.3307	0.7705	0.9664	0.8963	0.5143	0.742	0.8432	0.2577	0.8134	0.8309	0.5667	0.809	0.8931	0.7732	0.8425	0.7577	0.8176	0.7806	0.8326
0.4881	49.0	24353	0.3237	0.7771	0.9655	0.9058	0.525	0.7485	0.8457	0.2593	0.8207	0.8383	0.5963	0.8163	0.8944	0.7878	0.8558	0.759	0.823	0.7843	0.8361
0.3637	50.0	24850	0.3246	0.7762	0.9647	0.9041	0.5141	0.7451	0.8517	0.2588	0.8173	0.8346	0.5741	0.8102	0.899	0.7824	0.8475	0.761	0.8216	0.7852	0.8348
0.3978	51.0	25347	0.3296	0.7744	0.9654	0.8952	0.5077	0.7459	0.8478	0.259	0.8172	0.8341	0.5519	0.8113	0.8954	0.7835	0.8475	0.7562	0.8223	0.7835	0.8324
0.3942	52.0	25844	0.3241	0.7808	0.9681	0.9075	0.5314	0.753	0.8568	0.2612	0.8214	0.8393	0.5815	0.8172	0.9023	0.7874	0.8533	0.7624	0.8223	0.7925	0.8424
0.4079	53.0	26341	0.3221	0.779	0.9708	0.9091	0.4946	0.7525	0.855	0.2598	0.8206	0.8377	0.5333	0.8162	0.9007	0.7867	0.8542	0.7583	0.8182	0.792	0.8408
0.3715	54.0	26838	0.3191	0.7831	0.969	0.9074	0.5022	0.7551	0.8596	0.2606	0.824	0.8417	0.5407	0.8199	0.9046	0.789	0.855	0.7646	0.8257	0.7957	0.8443
0.4328	55.0	27335	0.3184	0.7799	0.9686	0.9057	0.5077	0.7512	0.8586	0.2598	0.8217	0.8396	0.5481	0.8172	0.9023	0.7878	0.8562	0.7579	0.8209	0.7939	0.8416
0.3676	56.0	27832	0.3192	0.7792	0.9683	0.9059	0.5051	0.7509	0.8561	0.2603	0.8218	0.8394	0.5481	0.8168	0.9007	0.7884	0.8562	0.7581	0.8223	0.791	0.8396
0.3737	57.0	28329	0.3174	0.7814	0.9677	0.9071	0.5052	0.7529	0.8579	0.2606	0.823	0.8406	0.5481	0.8182	0.9023	0.7884	0.8558	0.7629	0.8243	0.7928	0.8416
0.3532	58.0	28826	0.3172	0.7813	0.9674	0.9062	0.5029	0.7531	0.8581	0.2607	0.8236	0.8407	0.5407	0.8179	0.9029	0.7897	0.8562	0.7617	0.825	0.7926	0.8408
0.356	59.0	29323	0.3172	0.7814	0.9672	0.9061	0.5029	0.7534	0.8587	0.2609	0.8236	0.8407	0.5407	0.818	0.9036	0.7887	0.8554	0.7616	0.825	0.794	0.8416
0.4282	60.0	29820	0.3172	0.7813	0.9672	0.9061	0.5029	0.7534	0.8581	0.2609	0.8237	0.8407	0.5407	0.8181	0.9033	0.7893	0.8558	0.7616	0.825	0.7929	0.8414

Framework versions

• Transformers 4.45.2
• Pytorch 2.4.1+cu121
• Datasets 2.19.2
• Tokenizers 0.20.0