second upload

eval_results.txt

@@ -0,0 +1,18 @@
+Output: {
+  "acc": 0.8732984293193717
+}
+Output: {
+  "acc": 0.8827225130890053
+}
+Output: {
+  "acc": 0.8890052356020942
+}
+Output: {
+  "acc": 0.8952879581151832
+}
+Output: {
+  "acc": 0.8879581151832461
+}
+Output: {
+  "acc": 0.8952879581151832
+}

pytorch_model.bin

@@ -1,3 +1,3 @@
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-size 438028566
+oid sha256:3a5e3b777b2bf714cdfae54d26a454f91bc0d3ef85849c1c5ba62c53ea927eee
+size 438028546

training_args.bin

@@ -1,3 +1,3 @@
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-size 815
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+size 879

training_args.json

@@ -1 +1 @@
-{"model_path": "bert-base-uncased", "output_dir": "finetuned_kaggle/", "data_dir": "./kaggle", "max_seq_length": 256, "epoch": 5, "local_rank": -1, "task_name": "kaggle", "overwrite_cache": false, "learning_rate": 5e-05, "adam_epsilon": 1e-08, "train_batch_size": 32, "eval_batch_size": 64, "weight_decay": 0.1, "n_gpu": 1, "device": "cuda"}
+{"model_path": "bert-base-uncased", "output_dir": "./finetuned_kaggle/", "data_dir": "./datasets/kaggle/", "max_seq_length": 256, "epoch": 5, "local_rank": -1, "task_name": "kaggle", "overwrite_cache": false, "learning_rate": 5e-05, "adam_epsilon": 1e-08, "train_batch_size": 16, "eval_batch_size": 64, "weight_decay": 0.1, "num_labels": 4, "train": true, "eval": true, "n_gpu": 1, "device": "cuda"}