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xlm-r_mtl_xglue_classification

Transformers
PyTorch
xlm-roberta
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xlm-r_mtl_xglue_classification
File size: 1,698 Bytes 
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{
  "_name_or_path": "xlm-roberta-base",
  "architectures": [
    "XLMRobertaMultiTask"
  ],
  "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,
  "initializer_range": 0.02,
  "intermediate_size": 3072,
  "label2id": {
    "nc": {
      "autos": 9.0,
      "entertainment": 6.0,
      "finance": 3.0,
      "foodanddrink": 0.0,
      "health": 7.0,
      "lifestyle": 4.0,
      "news": 5.0,
      "sports": 1.0,
      "travel": 2.0,
      "video": 8.0
    },
    "paws-x": {
      "different": 0.0,
      "same": 1.0
    },
    "qadsm": {
      "Bad": 0.0,
      "Good": 1.0
    },
    "qam": {
      "False": 0.0,
      "True": 1.0
    },
    "wpr": {
      "Bad": 0.0,
      "Excellent": 3.0,
      "Fair": 1.0,
      "Good": 2.0,
      "Perfect": 4.0
    },
    "xnli": {
      "contradiction": 2.0,
      "entailment": 0.0,
      "neutral": 1.0
    }
  },
  "layer_norm_eps": 1e-05,
  "max_position_embeddings": 514,
  "model_type": "xlm-roberta",
  "num_accum_batches": 2,
  "num_attention_heads": 12,
  "num_hidden_layers": 12,
  "output_past": true,
  "pad_token_id": 1,
  "position_embedding_type": "absolute",
  "r3f": true,
  "r4f": false,
  "retain_gradients": false,
  "scale_loss": true,
  "tasks": [
    [
      "xnli",
      3
    ],
    [
      "paws-x",
      2
    ],
    [
      "nc",
      10
    ],
    [
      "qadsm",
      2
    ],
    [
      "wpr",
      5
    ],
    [
      "qam",
      2
    ]
  ],
  "torch_dtype": "float32",
  "transformers_version": "4.28.1",
  "type_vocab_size": 1,
  "use_cache": true,
  "vocab_size": 250002
}