iproskurina commited on May 28, 2023

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README.md +57 -0
all_results.json +15 -0
barcodes/dev_part1of1.json +0 -0
barcodes/test_part1of1.json +0 -0
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config.json +34 -0
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README.md ADDED Viewed

	@@ -0,0 +1,57 @@

+---
+license: mit
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: bert-base-italian-cased-ita-cola_64_3e-05_lr_0.01_decay_balanced
+  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. -->
+# bert-base-italian-cased-ita-cola_64_3e-05_lr_0.01_decay_balanced
+This model is a fine-tuned version of [dbmdz/bert-base-italian-cased](https://huggingface.co/dbmdz/bert-base-italian-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5797
+- Accuracy: 0.8668
+- Mcc: 0.4265
+## 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: 3e-05
+- train_batch_size: 64
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3.0
+### Training results
+### Framework versions
+- Transformers 4.23.0.dev0
+- Pytorch 1.12.1+cu113
+- Datasets 2.5.1
+- Tokenizers 0.13.0

all_results.json ADDED Viewed

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+{
+    "epoch": 3.0,
+    "eval_accuracy": 0.8668076109936576,
+    "eval_loss": 0.5796818733215332,
+    "eval_mcc": 0.42654879743004886,
+    "eval_runtime": 8.3787,
+    "eval_samples": 946,
+    "eval_samples_per_second": 112.905,
+    "eval_steps_per_second": 14.203,
+    "train_loss": 0.5242387531885032,
+    "train_runtime": 483.6259,
+    "train_samples": 7801,
+    "train_samples_per_second": 48.391,
+    "train_steps_per_second": 0.757
+}

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config.json ADDED Viewed

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+{
+  "_name_or_path": "dbmdz/bert-base-italian-cased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": 0,
+    "1": 1
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "0": 0,
+    "1": 1
+  },
+  "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",
+  "torch_dtype": "float32",
+  "transformers_version": "4.23.0.dev0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 31102
+}

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+{
+    "epoch": 3.0,
+    "eval_accuracy": 0.8668076109936576,
+    "eval_loss": 0.5796818733215332,
+    "eval_mcc": 0.42654879743004886,
+    "eval_runtime": 8.3787,
+    "eval_samples": 946,
+    "eval_samples_per_second": 112.905,
+    "eval_steps_per_second": 14.203
+}

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