End of training

README.md

@@ -2,6 +2,8 @@
 library_name: transformers
 base_model: google/mobilenet_v2_1.0_224
 tags:
+- image-classification
+- vision
 - generated_from_trainer
 metrics:
 - accuracy
@@ -18,28 +20,28 @@ should probably proofread and complete it, then remove this comment. -->
 
 # mobilenetv2-typecoffee-6
 
-This model is a fine-tuned version of [google/mobilenet_v2_1.0_224](https://huggingface.co/google/mobilenet_v2_1.0_224) on an unknown dataset.
+This model is a fine-tuned version of [google/mobilenet_v2_1.0_224](https://huggingface.co/google/mobilenet_v2_1.0_224) on the Master-Rapha7/TypeCoffee_16x16 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.8486
-- Accuracy: 0.6184
-- Precision: 0.6367
-- Recall: 0.6194
-- F1: 0.6204
-- Precision Durariadorio 16x16: 0.5979
-- Recall Durariadorio 16x16: 0.5512
-- F1 Durariadorio 16x16: 0.5736
-- Precision Mole 16x16: 0.5639
-- Recall Mole 16x16: 0.7756
-- F1 Mole 16x16: 0.6530
-- Precision Quebrado 16x16: 0.8543
-- Recall Quebrado 16x16: 0.6081
-- F1 Quebrado 16x16: 0.7104
-- Precision Riadorio 16x16: 0.5330
-- Recall Riadorio 16x16: 0.5312
-- F1 Riadorio 16x16: 0.5321
-- Precision Riofechado 16x16: 0.6344
-- Recall Riofechado 16x16: 0.6308
-- F1 Riofechado 16x16: 0.6326
+- Loss: 0.9977
+- Accuracy: 0.6484
+- Precision: 0.6521
+- Recall: 0.6499
+- F1: 0.6481
+- Precision Durariadorio 16x16: 0.6117
+- Recall Durariadorio 16x16: 0.6476
+- F1 Durariadorio 16x16: 0.6291
+- Precision Mole 16x16: 0.6444
+- Recall Mole 16x16: 0.7439
+- F1 Mole 16x16: 0.6906
+- Precision Quebrado 16x16: 0.7168
+- Recall Quebrado 16x16: 0.7635
+- F1 Quebrado 16x16: 0.7394
+- Precision Riadorio 16x16: 0.5405
+- Recall Riadorio 16x16: 0.5049
+- F1 Riadorio 16x16: 0.5221
+- Precision Riofechado 16x16: 0.7474
+- Recall Riofechado 16x16: 0.5896
+- F1 Riofechado 16x16: 0.6591
 
 ## Model description
 

all_results.json

@@ -0,0 +1,31 @@
+{
+    "epoch": 100.0,
+    "eval_accuracy": 0.6484254001032524,
+    "eval_f1": 0.6480692080859816,
+    "eval_f1_DuraRiadoRio_16x16": 0.6291376765760067,
+    "eval_f1_Mole_16x16": 0.6905721192586624,
+    "eval_f1_Quebrado_16x16": 0.739386296763346,
+    "eval_f1_RiadoRio_16x16": 0.5221088435374149,
+    "eval_f1_RioFechado_16x16": 0.6591411042944785,
+    "eval_loss": 0.9976791739463806,
+    "eval_precision": 0.6521451197878377,
+    "eval_precision_DuraRiadoRio_16x16": 0.6117261172611727,
+    "eval_precision_Mole_16x16": 0.6443609022556391,
+    "eval_precision_Quebrado_16x16": 0.7167889160554197,
+    "eval_precision_RiadoRio_16x16": 0.5404929577464789,
+    "eval_precision_RioFechado_16x16": 0.7473567056204786,
+    "eval_recall": 0.6498868731997905,
+    "eval_recall_DuraRiadoRio_16x16": 0.6475694444444444,
+    "eval_recall_Mole_16x16": 0.7439236111111112,
+    "eval_recall_Quebrado_16x16": 0.7634548611111112,
+    "eval_recall_RiadoRio_16x16": 0.5049342105263158,
+    "eval_recall_RioFechado_16x16": 0.5895522388059702,
+    "eval_runtime": 45.1355,
+    "eval_samples_per_second": 257.491,
+    "eval_steps_per_second": 16.107,
+    "total_flos": 2.446223378542756e+19,
+    "train_loss": 0.8178866318153334,
+    "train_runtime": 92994.6535,
+    "train_samples_per_second": 99.983,
+    "train_steps_per_second": 6.25
+}

eval_results.json

@@ -0,0 +1,26 @@
+{
+    "epoch": 100.0,
+    "eval_accuracy": 0.6484254001032524,
+    "eval_f1": 0.6480692080859816,
+    "eval_f1_DuraRiadoRio_16x16": 0.6291376765760067,
+    "eval_f1_Mole_16x16": 0.6905721192586624,
+    "eval_f1_Quebrado_16x16": 0.739386296763346,
+    "eval_f1_RiadoRio_16x16": 0.5221088435374149,
+    "eval_f1_RioFechado_16x16": 0.6591411042944785,
+    "eval_loss": 0.9976791739463806,
+    "eval_precision": 0.6521451197878377,
+    "eval_precision_DuraRiadoRio_16x16": 0.6117261172611727,
+    "eval_precision_Mole_16x16": 0.6443609022556391,
+    "eval_precision_Quebrado_16x16": 0.7167889160554197,
+    "eval_precision_RiadoRio_16x16": 0.5404929577464789,
+    "eval_precision_RioFechado_16x16": 0.7473567056204786,
+    "eval_recall": 0.6498868731997905,
+    "eval_recall_DuraRiadoRio_16x16": 0.6475694444444444,
+    "eval_recall_Mole_16x16": 0.7439236111111112,
+    "eval_recall_Quebrado_16x16": 0.7634548611111112,
+    "eval_recall_RiadoRio_16x16": 0.5049342105263158,
+    "eval_recall_RioFechado_16x16": 0.5895522388059702,
+    "eval_runtime": 45.1355,
+    "eval_samples_per_second": 257.491,
+    "eval_steps_per_second": 16.107
+}

train_results.json

@@ -0,0 +1,8 @@
+{
+    "epoch": 100.0,
+    "total_flos": 2.446223378542756e+19,
+    "train_loss": 0.8178866318153334,
+    "train_runtime": 92994.6535,
+    "train_samples_per_second": 99.983,
+    "train_steps_per_second": 6.25
+}