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@@ -32,3 +32,4 @@ 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
+eval_nbest_predictions.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,53 @@
+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- squad_v2
+model-index:
+- name: wd_0.01_bs_24_lr_2e-05_epochs_4
+  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. -->
+
+# wd_0.01_bs_24_lr_2e-05_epochs_4
+
+This model is a fine-tuned version of [xlnet-large-cased](https://huggingface.co/xlnet-large-cased) on the squad_v2 dataset.
+
+## 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: 72
+- eval_batch_size: 192
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4.0
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.27.4
+- Pytorch 1.13.1
+- Datasets 2.11.0
+- Tokenizers 0.11.0

all_results.json

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+    "eval_best_exact": 83.42457677082456,
+    "eval_best_exact_thresh": -11.09831714630127,
+    "eval_best_f1": 87.02545252526976,
+    "eval_best_f1_thresh": -11.09831714630127,
+    "eval_exact": 82.39703529015414,
+    "eval_f1": 86.19380952963157,
+    "eval_runtime": 207.3538,
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+    "eval_samples_per_second": 58.986,
+    "eval_steps_per_second": 0.309,
+    "eval_total": 11873,
+    "train_loss": 0.4368036111282407,
+    "train_runtime": 19719.8453,
+    "train_samples": 132240,
+    "train_samples_per_second": 26.824,
+    "train_steps_per_second": 0.373
+}

config.json

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+{
+  "_name_or_path": "xlnet-large-cased",
+  "architectures": [
+    "XLNetForQuestionAnswering"
+  ],
+  "attn_type": "bi",
+  "bi_data": false,
+  "bos_token_id": 1,
+  "clamp_len": -1,
+  "d_head": 64,
+  "d_inner": 4096,
+  "d_model": 1024,
+  "dropout": 0.1,
+  "end_n_top": 5,
+  "eos_token_id": 2,
+  "ff_activation": "gelu",
+  "initializer_range": 0.02,
+  "layer_norm_eps": 1e-12,
+  "mem_len": null,
+  "model_type": "xlnet",
+  "n_head": 16,
+  "n_layer": 24,
+  "pad_token_id": 5,
+  "reuse_len": null,
+  "same_length": false,
+  "start_n_top": 5,
+  "summary_activation": "tanh",
+  "summary_last_dropout": 0.1,
+  "summary_type": "last",
+  "summary_use_proj": true,
+  "task_specific_params": {
+    "text-generation": {
+      "do_sample": true,
+      "max_length": 250
+    }
+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.27.4",
+  "untie_r": true,
+  "use_mems_eval": true,
+  "use_mems_train": false,
+  "vocab_size": 32000
+}

eval_nbest_predictions.json

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eval_results.json

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+    "eval_HasAns_total": 5928,
+    "eval_NoAns_exact": 84.50798990748528,
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+}

pytorch_model.bin

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special_tokens_map.json

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+    "<eop>",
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+  "bos_token": "<s>",
+  "cls_token": "<cls>",
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+    "single_word": false
+  },
+  "pad_token": "<pad>",
+  "sep_token": "<sep>",
+  "unk_token": "<unk>"
+}

tokenizer_config.json

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+    "<eod>"
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+  "tokenizer_class": "XLNetTokenizer",
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+}

train_results.json

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+}

trainer_state.json

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training_args.bin

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