Evaluation on the test set completed on 2024_09_08.

README.md

@@ -0,0 +1,156 @@
+---
+license: apache-2.0
+base_model: facebook/dinov2-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: DinoVdeau-large-2024_09_05-batch-size32_epochs150_freeze
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# DinoVdeau-large-2024_09_05-batch-size32_epochs150_freeze
+
+This model is a fine-tuned version of [facebook/dinov2-large](https://huggingface.co/facebook/dinov2-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1209
+- F1 Micro: 0.8228
+- F1 Macro: 0.7175
+- Roc Auc: 0.8813
+- Accuracy: 0.3111
+- Learning Rate: 0.0000
+
+## 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: 0.001
+- 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: 150
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | F1 Micro | F1 Macro | Roc Auc | Accuracy | Rate   |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-------:|:--------:|:------:|
+| No log        | 1.0   | 273   | 0.1690          | 0.7517   | 0.5430   | 0.8384  | 0.2231   | 0.001  |
+| 0.2719        | 2.0   | 546   | 0.1538          | 0.7657   | 0.5721   | 0.8396  | 0.2401   | 0.001  |
+| 0.2719        | 3.0   | 819   | 0.1483          | 0.7773   | 0.6138   | 0.8516  | 0.2346   | 0.001  |
+| 0.1694        | 4.0   | 1092  | 0.1480          | 0.7723   | 0.6225   | 0.8407  | 0.2495   | 0.001  |
+| 0.1694        | 5.0   | 1365  | 0.1458          | 0.7797   | 0.6302   | 0.8470  | 0.2495   | 0.001  |
+| 0.1625        | 6.0   | 1638  | 0.1450          | 0.7798   | 0.6093   | 0.8477  | 0.2481   | 0.001  |
+| 0.1625        | 7.0   | 1911  | 0.1475          | 0.7767   | 0.6248   | 0.8454  | 0.2526   | 0.001  |
+| 0.1592        | 8.0   | 2184  | 0.1457          | 0.7804   | 0.6249   | 0.8521  | 0.2574   | 0.001  |
+| 0.1592        | 9.0   | 2457  | 0.1417          | 0.7869   | 0.6526   | 0.8561  | 0.2574   | 0.001  |
+| 0.157         | 10.0  | 2730  | 0.1436          | 0.7757   | 0.6290   | 0.8403  | 0.2547   | 0.001  |
+| 0.1563        | 11.0  | 3003  | 0.1428          | 0.7887   | 0.6448   | 0.8569  | 0.2640   | 0.001  |
+| 0.1563        | 12.0  | 3276  | 0.1439          | 0.7905   | 0.6493   | 0.8638  | 0.2581   | 0.001  |
+| 0.1558        | 13.0  | 3549  | 0.1391          | 0.7907   | 0.6562   | 0.8551  | 0.2713   | 0.001  |
+| 0.1558        | 14.0  | 3822  | 0.1409          | 0.7838   | 0.6338   | 0.8485  | 0.2644   | 0.001  |
+| 0.1543        | 15.0  | 4095  | 0.1396          | 0.7907   | 0.6463   | 0.8603  | 0.2578   | 0.001  |
+| 0.1543        | 16.0  | 4368  | 0.1390          | 0.7913   | 0.6594   | 0.8564  | 0.2654   | 0.001  |
+| 0.1535        | 17.0  | 4641  | 0.1418          | 0.7940   | 0.6586   | 0.8665  | 0.2564   | 0.001  |
+| 0.1535        | 18.0  | 4914  | 0.1416          | 0.7957   | 0.6560   | 0.8646  | 0.2658   | 0.001  |
+| 0.1549        | 19.0  | 5187  | 0.1403          | 0.7886   | 0.6524   | 0.8536  | 0.2630   | 0.001  |
+| 0.1549        | 20.0  | 5460  | 0.1476          | 0.7911   | 0.6558   | 0.8568  | 0.2613   | 0.001  |
+| 0.154         | 21.0  | 5733  | 0.1429          | 0.7880   | 0.6397   | 0.8568  | 0.2658   | 0.001  |
+| 0.1529        | 22.0  | 6006  | 0.1414          | 0.7937   | 0.6508   | 0.8654  | 0.2613   | 0.001  |
+| 0.1529        | 23.0  | 6279  | 0.1415          | 0.7976   | 0.6618   | 0.8613  | 0.2685   | 0.0001 |
+| 0.1449        | 24.0  | 6552  | 0.1323          | 0.8045   | 0.6751   | 0.8665  | 0.2789   | 0.0001 |
+| 0.1449        | 25.0  | 6825  | 0.1310          | 0.8044   | 0.6724   | 0.8688  | 0.2793   | 0.0001 |
+| 0.1416        | 26.0  | 7098  | 0.1327          | 0.8036   | 0.6689   | 0.8646  | 0.2821   | 0.0001 |
+| 0.1416        | 27.0  | 7371  | 0.1317          | 0.8069   | 0.6797   | 0.8715  | 0.2817   | 0.0001 |
+| 0.1391        | 28.0  | 7644  | 0.1288          | 0.8072   | 0.6818   | 0.8698  | 0.2775   | 0.0001 |
+| 0.1391        | 29.0  | 7917  | 0.1294          | 0.8038   | 0.6808   | 0.8629  | 0.2845   | 0.0001 |
+| 0.138         | 30.0  | 8190  | 0.1294          | 0.8077   | 0.6826   | 0.8702  | 0.2859   | 0.0001 |
+| 0.138         | 31.0  | 8463  | 0.1274          | 0.8074   | 0.6779   | 0.8666  | 0.2879   | 0.0001 |
+| 0.1364        | 32.0  | 8736  | 0.1278          | 0.8104   | 0.6869   | 0.8728  | 0.2883   | 0.0001 |
+| 0.1359        | 33.0  | 9009  | 0.1277          | 0.8077   | 0.6811   | 0.8692  | 0.2869   | 0.0001 |
+| 0.1359        | 34.0  | 9282  | 0.1266          | 0.8109   | 0.6874   | 0.8714  | 0.2883   | 0.0001 |
+| 0.1341        | 35.0  | 9555  | 0.1262          | 0.8104   | 0.6885   | 0.8716  | 0.2904   | 0.0001 |
+| 0.1341        | 36.0  | 9828  | 0.1269          | 0.8070   | 0.6876   | 0.8657  | 0.2827   | 0.0001 |
+| 0.1339        | 37.0  | 10101 | 0.1266          | 0.8082   | 0.6834   | 0.8678  | 0.2866   | 0.0001 |
+| 0.1339        | 38.0  | 10374 | 0.1255          | 0.8106   | 0.6936   | 0.8707  | 0.2956   | 0.0001 |
+| 0.1307        | 39.0  | 10647 | 0.1249          | 0.8142   | 0.6986   | 0.8768  | 0.2928   | 0.0001 |
+| 0.1307        | 40.0  | 10920 | 0.1258          | 0.8138   | 0.6990   | 0.8773  | 0.2935   | 0.0001 |
+| 0.1317        | 41.0  | 11193 | 0.1253          | 0.8101   | 0.6924   | 0.8688  | 0.2924   | 0.0001 |
+| 0.1317        | 42.0  | 11466 | 0.1244          | 0.8138   | 0.6970   | 0.8738  | 0.3004   | 0.0001 |
+| 0.1308        | 43.0  | 11739 | 0.1245          | 0.8131   | 0.6956   | 0.8734  | 0.2949   | 0.0001 |
+| 0.1307        | 44.0  | 12012 | 0.1250          | 0.8130   | 0.6915   | 0.8743  | 0.2966   | 0.0001 |
+| 0.1307        | 45.0  | 12285 | 0.1240          | 0.8137   | 0.7051   | 0.8740  | 0.2963   | 0.0001 |
+| 0.1295        | 46.0  | 12558 | 0.1241          | 0.8131   | 0.6988   | 0.8733  | 0.2976   | 0.0001 |
+| 0.1295        | 47.0  | 12831 | 0.1243          | 0.8119   | 0.6958   | 0.8716  | 0.2956   | 0.0001 |
+| 0.1293        | 48.0  | 13104 | 0.1239          | 0.8135   | 0.6990   | 0.8744  | 0.2956   | 0.0001 |
+| 0.1293        | 49.0  | 13377 | 0.1243          | 0.8153   | 0.7007   | 0.8775  | 0.2997   | 0.0001 |
+| 0.1274        | 50.0  | 13650 | 0.1241          | 0.8152   | 0.7000   | 0.8769  | 0.2980   | 0.0001 |
+| 0.1274        | 51.0  | 13923 | 0.1248          | 0.8153   | 0.7056   | 0.8803  | 0.3011   | 0.0001 |
+| 0.1271        | 52.0  | 14196 | 0.1243          | 0.8157   | 0.7036   | 0.8751  | 0.3049   | 0.0001 |
+| 0.1271        | 53.0  | 14469 | 0.1241          | 0.8153   | 0.7032   | 0.8778  | 0.3021   | 0.0001 |
+| 0.1275        | 54.0  | 14742 | 0.1234          | 0.8152   | 0.7068   | 0.8753  | 0.3021   | 0.0001 |
+| 0.1256        | 55.0  | 15015 | 0.1231          | 0.8166   | 0.7076   | 0.8776  | 0.3018   | 0.0001 |
+| 0.1256        | 56.0  | 15288 | 0.1228          | 0.8190   | 0.7088   | 0.8822  | 0.3067   | 0.0001 |
+| 0.1258        | 57.0  | 15561 | 0.1226          | 0.8160   | 0.7080   | 0.8767  | 0.3070   | 0.0001 |
+| 0.1258        | 58.0  | 15834 | 0.1233          | 0.8170   | 0.7073   | 0.8773  | 0.3021   | 0.0001 |
+| 0.1258        | 59.0  | 16107 | 0.1227          | 0.8172   | 0.7135   | 0.8781  | 0.3021   | 0.0001 |
+| 0.1258        | 60.0  | 16380 | 0.1233          | 0.8143   | 0.7040   | 0.8729  | 0.3021   | 0.0001 |
+| 0.1252        | 61.0  | 16653 | 0.1234          | 0.8168   | 0.7121   | 0.8784  | 0.3042   | 0.0001 |
+| 0.1252        | 62.0  | 16926 | 0.1223          | 0.8169   | 0.7125   | 0.8764  | 0.3049   | 0.0001 |
+| 0.1238        | 63.0  | 17199 | 0.1231          | 0.8151   | 0.7090   | 0.8752  | 0.3035   | 0.0001 |
+| 0.1238        | 64.0  | 17472 | 0.1228          | 0.8183   | 0.7114   | 0.8785  | 0.3067   | 0.0001 |
+| 0.1247        | 65.0  | 17745 | 0.1231          | 0.8185   | 0.7156   | 0.8802  | 0.3035   | 0.0001 |
+| 0.123         | 66.0  | 18018 | 0.1225          | 0.8193   | 0.7084   | 0.8809  | 0.3021   | 0.0001 |
+| 0.123         | 67.0  | 18291 | 0.1222          | 0.8186   | 0.7136   | 0.8814  | 0.3032   | 0.0001 |
+| 0.1224        | 68.0  | 18564 | 0.1220          | 0.8201   | 0.7169   | 0.8818  | 0.3091   | 0.0001 |
+| 0.1224        | 69.0  | 18837 | 0.1228          | 0.8171   | 0.7165   | 0.8768  | 0.3018   | 0.0001 |
+| 0.1228        | 70.0  | 19110 | 0.1227          | 0.8177   | 0.7131   | 0.8765  | 0.3042   | 0.0001 |
+| 0.1228        | 71.0  | 19383 | 0.1232          | 0.8155   | 0.7123   | 0.8733  | 0.2980   | 0.0001 |
+| 0.1224        | 72.0  | 19656 | 0.1222          | 0.8177   | 0.7181   | 0.8780  | 0.3056   | 0.0001 |
+| 0.1224        | 73.0  | 19929 | 0.1221          | 0.8162   | 0.7047   | 0.8760  | 0.3077   | 0.0001 |
+| 0.122         | 74.0  | 20202 | 0.1230          | 0.8148   | 0.7070   | 0.8732  | 0.2973   | 0.0001 |
+| 0.122         | 75.0  | 20475 | 0.1214          | 0.8176   | 0.7124   | 0.8768  | 0.3049   | 1e-05  |
+| 0.1201        | 76.0  | 20748 | 0.1209          | 0.8213   | 0.7265   | 0.8828  | 0.3067   | 1e-05  |
+| 0.1192        | 77.0  | 21021 | 0.1216          | 0.8221   | 0.7249   | 0.8860  | 0.3073   | 1e-05  |
+| 0.1192        | 78.0  | 21294 | 0.1211          | 0.8210   | 0.7233   | 0.8828  | 0.3056   | 1e-05  |
+| 0.1178        | 79.0  | 21567 | 0.1211          | 0.8181   | 0.7158   | 0.8769  | 0.3056   | 1e-05  |
+| 0.1178        | 80.0  | 21840 | 0.1210          | 0.8200   | 0.7197   | 0.8824  | 0.3091   | 1e-05  |
+| 0.1178        | 81.0  | 22113 | 0.1205          | 0.8190   | 0.7194   | 0.8784  | 0.3105   | 1e-05  |
+| 0.1178        | 82.0  | 22386 | 0.1205          | 0.8187   | 0.7213   | 0.8782  | 0.3070   | 1e-05  |
+| 0.1162        | 83.0  | 22659 | 0.1215          | 0.8171   | 0.7136   | 0.8754  | 0.3049   | 1e-05  |
+| 0.1162        | 84.0  | 22932 | 0.1209          | 0.8212   | 0.7226   | 0.8817  | 0.3115   | 1e-05  |
+| 0.1174        | 85.0  | 23205 | 0.1206          | 0.8213   | 0.7219   | 0.8823  | 0.3094   | 1e-05  |
+| 0.1174        | 86.0  | 23478 | 0.1210          | 0.8207   | 0.7256   | 0.8811  | 0.3084   | 1e-05  |
+| 0.1167        | 87.0  | 23751 | 0.1210          | 0.8192   | 0.7163   | 0.8800  | 0.3073   | 1e-05  |
+| 0.116         | 88.0  | 24024 | 0.1208          | 0.8219   | 0.7180   | 0.8831  | 0.3094   | 1e-05  |
+| 0.116         | 89.0  | 24297 | 0.1213          | 0.8236   | 0.7293   | 0.8872  | 0.3125   | 0.0000 |
+| 0.1161        | 90.0  | 24570 | 0.1211          | 0.8228   | 0.7250   | 0.8869  | 0.3108   | 0.0000 |
+| 0.1161        | 91.0  | 24843 | 0.1206          | 0.8191   | 0.7187   | 0.8779  | 0.3105   | 0.0000 |
+| 0.1162        | 92.0  | 25116 | 0.1208          | 0.8196   | 0.7150   | 0.8793  | 0.3105   | 0.0000 |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

all_results.json

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+    "train_steps_per_second": 0.21
+}

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test_results.json

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train_results.json

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trainer_state.json

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