msgfrom96/xlm_emo_multi

.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 +1,71 @@
+---
+library_name: transformers
+license: mit
+base_model: xlm-roberta-base
+tags:
+- generated_from_trainer
+model-index:
+- name: emotion_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. -->
+
+# emotion_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: 0.3094
+- Micro F1: 0.6854
+- Macro F1: 0.4971
+
+## 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: 1.5e-05
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Micro F1 | Macro F1 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
+| 0.5206        | 1.0   | 143  | 0.4242          | 0.3130   | 0.1419   |
+| 0.3877        | 2.0   | 286  | 0.3661          | 0.6053   | 0.3646   |
+| 0.3538        | 3.0   | 429  | 0.3528          | 0.6106   | 0.3874   |
+| 0.3306        | 4.0   | 572  | 0.3341          | 0.6563   | 0.4442   |
+| 0.3055        | 5.0   | 715  | 0.3254          | 0.6761   | 0.4663   |
+| 0.2865        | 6.0   | 858  | 0.3222          | 0.6776   | 0.4853   |
+| 0.2811        | 7.0   | 1001 | 0.3169          | 0.6804   | 0.4766   |
+| 0.2718        | 8.0   | 1144 | 0.3154          | 0.6808   | 0.4874   |
+| 0.2673        | 9.0   | 1287 | 0.3175          | 0.6802   | 0.4922   |
+| 0.2646        | 10.0  | 1430 | 0.3166          | 0.6827   | 0.4955   |
+
+
+### Framework versions
+
+- Transformers 4.48.2
+- Pytorch 2.3.1.post300
+- Datasets 2.2.1
+- Tokenizers 0.21.0

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": "anger",
+    "1": "anticipation",
+    "2": "disgust",
+    "3": "fear",
+    "4": "joy",
+    "5": "sadness",
+    "6": "surprise",
+    "7": "trust",
+    "8": "love",
+    "9": "optimism",
+    "10": "pessimism"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "anger": 0,
+    "anticipation": 1,
+    "disgust": 2,
+    "fear": 3,
+    "joy": 4,
+    "love": 8,
+    "optimism": 9,
+    "pessimism": 10,
+    "sadness": 5,
+    "surprise": 6,
+    "trust": 7
+  },
+  "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": "multi_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.48.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

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special_tokens_map.json

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xlm_multi_emo/config.json

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+  "_name_or_path": "xlm-roberta-base",
+  "architectures": [
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+  ],
+  "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": "anger",
+    "1": "anticipation",
+    "2": "disgust",
+    "3": "fear",
+    "4": "joy",
+    "5": "sadness",
+    "6": "surprise",
+    "7": "trust",
+    "8": "love",
+    "9": "optimism",
+    "10": "pessimism"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
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+    "anticipation": 1,
+    "disgust": 2,
+    "fear": 3,
+    "joy": 4,
+    "love": 8,
+    "optimism": 9,
+    "pessimism": 10,
+    "sadness": 5,
+    "surprise": 6,
+    "trust": 7
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+  "model_type": "xlm-roberta",
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+  "problem_type": "multi_label_classification",
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+  "transformers_version": "4.48.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

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