roberta-sentiment

README.md

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+---
+library_name: transformers
+license: mit
+base_model: FacebookAI/xlm-roberta-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: best-model-v1
+  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. -->
+
+# best-model-v1
+
+This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6069
+- Accuracy: 0.4410
+- Precision: 0.5118
+- Recall: 0.6489
+- F1 Score: 0.5711
+
+## 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: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine_with_restarts
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
+| 1.7357        | 0.3911 | 500  | 0.8218          | 0.3192   | 0.2798    | 0.2506 | 0.2551   |
+| 1.5848        | 0.7822 | 1000 | 0.7275          | 0.3937   | 0.4789    | 0.4157 | 0.4387   |
+| 1.398         | 1.1729 | 1500 | 0.6628          | 0.4123   | 0.4885    | 0.5846 | 0.5251   |
+| 1.2999        | 1.5639 | 2000 | 0.6264          | 0.4295   | 0.5046    | 0.6402 | 0.5626   |
+| 1.2964        | 1.9550 | 2500 | 0.6101          | 0.4260   | 0.4991    | 0.6553 | 0.5655   |
+| 1.2479        | 2.3457 | 3000 | 0.6069          | 0.4381   | 0.5082    | 0.6506 | 0.5695   |
+| 1.267         | 2.7368 | 3500 | 0.6069          | 0.4410   | 0.5118    | 0.6489 | 0.5711   |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.4.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

config.json

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+{
+  "_name_or_path": "FacebookAI/xlm-roberta-large",
+  "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": 1024,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "multi_label_classification",
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.47.1",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

model.safetensors

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+size 1119839626

training_args.bin

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