End of training

README.md

@@ -0,0 +1,68 @@
+---
+base_model: klue/roberta-small
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: mainCut-label9
+  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. -->
+
+# mainCut-label9
+
+This model is a fine-tuned version of [klue/roberta-small](https://huggingface.co/klue/roberta-small) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1075
+- Accuracy: 0.6309
+
+## 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: 5e-05
+- 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: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.2286        | 0.4   | 500  | 1.2054          | 0.5685   |
+| 1.2387        | 0.8   | 1000 | 1.1320          | 0.6062   |
+| 0.9892        | 1.2   | 1500 | 1.1341          | 0.6169   |
+| 1.1259        | 1.6   | 2000 | 1.1117          | 0.6202   |
+| 0.9904        | 2.0   | 2500 | 1.0929          | 0.6262   |
+| 1.0053        | 2.4   | 3000 | 1.1021          | 0.6243   |
+| 0.9492        | 2.8   | 3500 | 1.0982          | 0.6251   |
+| 0.9811        | 3.2   | 4000 | 1.1167          | 0.6238   |
+| 0.9258        | 3.6   | 4500 | 1.1068          | 0.6341   |
+| 0.8481        | 4.0   | 5000 | 1.1075          | 0.6309   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.0.1
+- Datasets 2.14.4
+- Tokenizers 0.13.3

config.json

@@ -0,0 +1,52 @@
+{
+  "_name_or_path": "klue/roberta-small",
+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6",
+    "7": "LABEL_7",
+    "8": "LABEL_8"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6,
+    "LABEL_7": 7,
+    "LABEL_8": 8
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 6,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "tokenizer_class": "BertTokenizer",
+  "torch_dtype": "float32",
+  "transformers_version": "4.32.1",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 32000
+}

pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e37224a773c982465ab154de047dadfe99c2ccd7f4db8cb369d1ac0cfc9ade74
+size 272425457

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dc662baf166efa56b7a5ae96ab249fa63434350f82299e407be59b02b512454e
+size 4027