commit files to HF hub

README.md

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----
-
-language: en
-tags:
-- sagemaker
-- bert-base-uncased
-- text classification
-license: apache-2.0
-datasets:
-- adecorpusv2
-model-index:
-- name: bert-base-uncased-ade_corpus
-  results:
-  - task: 
-      name: Text Classification
-      type: text-classification
-    dataset:
-      name: "ade_corpus_v2Ade_corpus_v2_classification" 
-      type: ade_corpus
-  
----
-
-## bert-base-uncased
-This model was trained using Amazon SageMaker and the new Hugging Face Deep Learning container.
-
-
-## Hyperparameters
-```json
-{
-    "do_eval": true,
-    "do_train": true,
-    "fp16": true,
-    "load_best_model_at_end": true,
-    "model_name": "bert-base-uncased",
-    "num_train_epochs": 10,
-    "per_device_eval_batch_size": 16,
-    "per_device_train_batch_size": 16,
-    "learning_rate":5e-5
-
-}
-```
-## Validation Metrics
-| key | value |
-| --- | ----- |
-| eval_accuracy  | 0.9298021697511167 |
-| eval_auc | 0.8902672664394546 |
-| eval_f1 | 0.827315541601256 |
-| eval_loss | 0.17835010588169098 |
-| eval_recall | 0.8234375 |
-| eval_precision | 0.831230283911672 |
-

config.json

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+{
+  "_name_or_path": "bert-base-uncased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "transformers_version": "4.6.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

eval_results.json

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+{
+ "epoch": 3.0, 
+ "eval_accuracy" : 0.9298021697511167, 
+ "eval_auc":0.8902672664394546, 
+ "eval_f1": 0.827315541601256, 
+ "eval_loss": 0.17835010588169098, 
+ "eval_mem_cpu_alloc_delta":6115328, 
+ "eval_mem_cpu_peaked_delta":49152,
+ "eval_mem_gpu_peaked_delta":2321744384, 
+ "eval_precision":0.831230283911672, 
+ "eval_recall":0.8234375, 
+ "eval_runtime":6.3601, 
+ "eval_samples_per_second":492.756
+}

eval_results.txt

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+epoch = 3.0
+eval_accuracy = 0.9298021697511167
+eval_auc = 0.8902672664394546
+eval_f1 = 0.827315541601256
+eval_loss = 0.17835010588169098
+eval_mem_cpu_alloc_delta = 6115328
+eval_mem_cpu_peaked_delta = 49152
+eval_mem_gpu_alloc_delta = 0
+eval_mem_gpu_peaked_delta = 2321744384
+eval_precision = 0.831230283911672
+eval_recall = 0.8234375
+eval_runtime = 6.3601
+eval_samples_per_second = 492.756

pytorch_model.bin

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special_tokens_map.json

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+{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

tokenizer_config.json

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+{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "bert-base-uncased"}

training_args.bin

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