End of training

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,69 @@
+---
+license: mit
+base_model: xlm-roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: my_awesome_model
+  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. -->
+
+# my_awesome_model
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0506
+- Accuracy: 0.6959
+
+## 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: 8e-06
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 383  | 1.6014          | 0.3719   |
+| 1.6917        | 2.0   | 766  | 1.1865          | 0.5951   |
+| 1.1046        | 3.0   | 1149 | 1.0636          | 0.6473   |
+| 0.9029        | 4.0   | 1532 | 1.0561          | 0.6603   |
+| 0.9029        | 5.0   | 1915 | 1.0121          | 0.6794   |
+| 0.765         | 6.0   | 2298 | 0.9676          | 0.7072   |
+| 0.6696        | 7.0   | 2681 | 0.9890          | 0.6985   |
+| 0.5756        | 8.0   | 3064 | 1.0216          | 0.7107   |
+| 0.5756        | 9.0   | 3447 | 1.0752          | 0.6881   |
+| 0.5302        | 10.0  | 3830 | 1.0506          | 0.6959   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1

config.json

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+{
+  "_name_or_path": "xlm-roberta-base",
+  "architectures": [
+    "XLMRobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "ANGRY",
+    "1": "FEAR",
+    "2": "HAPPY",
+    "3": "HATE",
+    "4": "OTHER",
+    "5": "SAD",
+    "6": "SURPRISE"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "ANGRY": 0,
+    "FEAR": 1,
+    "HAPPY": 2,
+    "HATE": 3,
+    "OTHER": 4,
+    "SAD": 5,
+    "SURPRISE": 6
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.35.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

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runs/Feb02_07-33-58_424a2b673929/events.out.tfevents.1706859239.424a2b673929.1003.0

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special_tokens_map.json

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tokenizer_config.json

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+}

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