{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "provenance": [], "gpuType": "T4" }, "kernelspec": { "name": "python3", "display_name": "Python 3" }, "language_info": { "name": "python" }, "accelerator": "GPU" }, "cells": [ { "cell_type": "markdown", "source": [ "# osiria/minilm-italian-l6-h384-question-answering\n", "## test set metrics" ], "metadata": { "id": "oub2ir8ZDkrH" } }, { "cell_type": "code", "execution_count": 1, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "02K9xO6Gvto1", "outputId": "3f72da34-6228-451a-c656-3f9fbb358e7f" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Collecting git+https://github.com/huggingface/transformers\n", " Cloning https://github.com/huggingface/transformers to /tmp/pip-req-build-zw2jat5c\n", " Running command git clone --filter=blob:none --quiet https://github.com/huggingface/transformers /tmp/pip-req-build-zw2jat5c\n", " Resolved https://github.com/huggingface/transformers to commit df5c5c62ae253055336f5bb0828ca8e3e15ab6bd\n", " Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", " Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers==4.36.0.dev0) (3.13.1)\n", "Requirement already satisfied: huggingface-hub<1.0,>=0.19.3 in /usr/local/lib/python3.10/dist-packages (from transformers==4.36.0.dev0) (0.19.4)\n", "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers==4.36.0.dev0) (1.23.5)\n", "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers==4.36.0.dev0) (23.2)\n", "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers==4.36.0.dev0) (6.0.1)\n", "Requirement already satisfied: regex!=2019.12.17 in 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], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "9OFz3JdR0cQ_", "outputId": "137e11b1-d6ce-4ba7-89b9-1ce61fac9964" }, "execution_count": 4, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Collecting evaluate\n", " Downloading evaluate-0.4.1-py3-none-any.whl (84 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m84.1/84.1 kB\u001b[0m \u001b[31m965.1 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: datasets>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from evaluate) (2.15.0)\n", "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from evaluate) (1.23.5)\n", "Requirement already satisfied: dill in /usr/local/lib/python3.10/dist-packages (from evaluate) (0.3.7)\n", "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from evaluate) (1.5.3)\n", "Requirement already satisfied: requests>=2.19.0 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--per_device_eval_batch_size=5 --output_dir eval_results" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "B5O5Lom8x_c4", "outputId": "285a1739-b358-4127-8429-5437f35682ae" }, "execution_count": 8, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "2023-12-09 13:05:00.034232: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", "2023-12-09 13:05:00.034295: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", "2023-12-09 13:05:00.034336: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", "2023-12-09 13:05:01.133400: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n", "12/09/2023 13:05:04 - WARNING - __main__ - Process rank: 0, device: cuda:0, n_gpu: 1, distributed training: False, 16-bits training: False\n", "12/09/2023 13:05:04 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", "_n_gpu=1,\n", "adafactor=False,\n", "adam_beta1=0.9,\n", "adam_beta2=0.999,\n", "adam_epsilon=1e-08,\n", "auto_find_batch_size=False,\n", "bf16=False,\n", "bf16_full_eval=False,\n", "data_seed=None,\n", "dataloader_drop_last=False,\n", "dataloader_num_workers=0,\n", "dataloader_persistent_workers=False,\n", "dataloader_pin_memory=True,\n", "ddp_backend=None,\n", "ddp_broadcast_buffers=None,\n", "ddp_bucket_cap_mb=None,\n", "ddp_find_unused_parameters=None,\n", "ddp_timeout=1800,\n", "debug=[],\n", "deepspeed=None,\n", "disable_tqdm=False,\n", "dispatch_batches=None,\n", "do_eval=False,\n", "do_predict=True,\n", "do_train=False,\n", "eval_accumulation_steps=None,\n", "eval_delay=0,\n", "eval_steps=None,\n", "evaluation_strategy=no,\n", "fp16=False,\n", "fp16_backend=auto,\n", "fp16_full_eval=False,\n", "fp16_opt_level=O1,\n", "fsdp=[],\n", "fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_grad_ckpt': False},\n", "fsdp_min_num_params=0,\n", "fsdp_transformer_layer_cls_to_wrap=None,\n", "full_determinism=False,\n", "gradient_accumulation_steps=1,\n", "gradient_checkpointing=False,\n", "gradient_checkpointing_kwargs=None,\n", "greater_is_better=None,\n", "group_by_length=False,\n", "half_precision_backend=auto,\n", "hub_always_push=False,\n", "hub_model_id=None,\n", "hub_private_repo=False,\n", "hub_strategy=every_save,\n", "hub_token=,\n", "ignore_data_skip=False,\n", "include_inputs_for_metrics=False,\n", "include_num_input_tokens_seen=False,\n", "include_tokens_per_second=False,\n", "jit_mode_eval=False,\n", "label_names=None,\n", "label_smoothing_factor=0.0,\n", "learning_rate=5e-05,\n", "length_column_name=length,\n", "load_best_model_at_end=False,\n", "local_rank=0,\n", "log_level=passive,\n", "log_level_replica=warning,\n", "log_on_each_node=True,\n", "logging_dir=eval_results/runs/Dec09_13-05-04_f36df394933d,\n", "logging_first_step=False,\n", "logging_nan_inf_filter=True,\n", "logging_steps=500,\n", "logging_strategy=steps,\n", "lr_scheduler_kwargs={},\n", "lr_scheduler_type=linear,\n", "max_grad_norm=1.0,\n", "max_steps=-1,\n", "metric_for_best_model=None,\n", "mp_parameters=,\n", "neftune_noise_alpha=None,\n", "no_cuda=False,\n", "num_train_epochs=3.0,\n", "optim=adamw_torch,\n", "optim_args=None,\n", "output_dir=eval_results,\n", "overwrite_output_dir=False,\n", "past_index=-1,\n", "per_device_eval_batch_size=5,\n", "per_device_train_batch_size=8,\n", "prediction_loss_only=False,\n", "push_to_hub=False,\n", "push_to_hub_model_id=None,\n", "push_to_hub_organization=None,\n", "push_to_hub_token=,\n", "ray_scope=last,\n", "remove_unused_columns=True,\n", "report_to=['tensorboard'],\n", "resume_from_checkpoint=None,\n", "run_name=eval_results,\n", "save_on_each_node=False,\n", "save_only_model=False,\n", "save_safetensors=True,\n", "save_steps=500,\n", "save_strategy=steps,\n", "save_total_limit=None,\n", "seed=42,\n", "skip_memory_metrics=True,\n", "split_batches=False,\n", "tf32=None,\n", "torch_compile=False,\n", "torch_compile_backend=None,\n", "torch_compile_mode=None,\n", "torchdynamo=None,\n", "tpu_metrics_debug=False,\n", "tpu_num_cores=None,\n", "use_cpu=False,\n", "use_ipex=False,\n", "use_legacy_prediction_loop=False,\n", "use_mps_device=False,\n", "warmup_ratio=0.0,\n", "warmup_steps=0,\n", "weight_decay=0.0,\n", ")\n", "https://huggingface.co/datasets/squad_it/resolve/main/squad_it.py not found in cache or force_download set to True, downloading to 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Downloading and preparing it from source\n", "12/09/2023 13:05:05 - INFO - datasets.builder - Dataset not on Hf google storage. Downloading and preparing it from source\n", "Downloading data files: 0% 0/2 [00:00> loading configuration file config.json from cache at /root/.cache/huggingface/hub/models--osiria--minilm-italian-l6-h384-question-answering/snapshots/1faf21988c80be33048fe9d3e0bb98aafec858bb/config.json\n", "[INFO|configuration_utils.py:802] 2023-12-09 13:05:15,613 >> Model config XLMRobertaConfig {\n", " \"_name_or_path\": \"osiria/minilm-italian-l6-h384-question-answering\",\n", " \"architectures\": [\n", " \"XLMRobertaForQuestionAnswering\"\n", " ],\n", " \"attention_probs_dropout_prob\": 0.1,\n", " \"bos_token_id\": 0,\n", " \"classifier_dropout\": null,\n", " \"eos_token_id\": 2,\n", " \"hidden_act\": \"gelu\",\n", " \"hidden_dropout_prob\": 0.1,\n", " \"hidden_size\": 384,\n", " \"initializer_range\": 0.02,\n", " \"intermediate_size\": 1536,\n", " \"layer_norm_eps\": 1e-05,\n", " \"max_position_embeddings\": 514,\n", " \"model_type\": \"xlm-roberta\",\n", " \"num_attention_heads\": 12,\n", " \"num_hidden_layers\": 6,\n", " \"pad_token_id\": 1,\n", " \"position_embedding_type\": \"absolute\",\n", " \"torch_dtype\": \"float32\",\n", " \"transformers_version\": \"4.36.0.dev0\",\n", " \"type_vocab_size\": 1,\n", " \"use_cache\": true,\n", " \"vocab_size\": 30498\n", "}\n", "\n", "tokenizer_config.json: 100% 418/418 [00:00<00:00, 2.73MB/s]\n", "tokenizer.json: 100% 1.39M/1.39M [00:00<00:00, 18.7MB/s]\n", "special_tokens_map.json: 100% 280/280 [00:00<00:00, 1.75MB/s]\n", "[INFO|tokenization_utils_base.py:2026] 2023-12-09 13:05:16,227 >> loading file sentencepiece.bpe.model from cache at None\n", "[INFO|tokenization_utils_base.py:2026] 2023-12-09 13:05:16,227 >> loading file tokenizer.json from cache at /root/.cache/huggingface/hub/models--osiria--minilm-italian-l6-h384-question-answering/snapshots/1faf21988c80be33048fe9d3e0bb98aafec858bb/tokenizer.json\n", "[INFO|tokenization_utils_base.py:2026] 2023-12-09 13:05:16,227 >> loading file added_tokens.json from cache at None\n", "[INFO|tokenization_utils_base.py:2026] 2023-12-09 13:05:16,227 >> loading file special_tokens_map.json from cache at /root/.cache/huggingface/hub/models--osiria--minilm-italian-l6-h384-question-answering/snapshots/1faf21988c80be33048fe9d3e0bb98aafec858bb/special_tokens_map.json\n", "[INFO|tokenization_utils_base.py:2026] 2023-12-09 13:05:16,228 >> loading file tokenizer_config.json from cache at /root/.cache/huggingface/hub/models--osiria--minilm-italian-l6-h384-question-answering/snapshots/1faf21988c80be33048fe9d3e0bb98aafec858bb/tokenizer_config.json\n", "pytorch_model.bin: 100% 90.3M/90.3M [00:01<00:00, 57.7MB/s]\n", "[INFO|modeling_utils.py:3299] 2023-12-09 13:05:18,490 >> loading weights file pytorch_model.bin from cache at /root/.cache/huggingface/hub/models--osiria--minilm-italian-l6-h384-question-answering/snapshots/1faf21988c80be33048fe9d3e0bb98aafec858bb/pytorch_model.bin\n", "[INFO|modeling_utils.py:4139] 2023-12-09 13:05:18,858 >> All model checkpoint weights were used when initializing XLMRobertaForQuestionAnswering.\n", "\n", "[INFO|modeling_utils.py:4147] 2023-12-09 13:05:18,858 >> All the weights of XLMRobertaForQuestionAnswering were initialized from the model checkpoint at osiria/minilm-italian-l6-h384-question-answering.\n", "If your task is similar to the task the model of the checkpoint was trained on, you can already use XLMRobertaForQuestionAnswering for predictions without further training.\n", "Running tokenizer on prediction dataset: 0% 0/7609 [00:00> The following columns in the test set don't have a corresponding argument in `XLMRobertaForQuestionAnswering.forward` and have been ignored: offset_mapping, example_id. If offset_mapping, example_id are not expected by `XLMRobertaForQuestionAnswering.forward`, you can safely ignore this message.\n", "[INFO|trainer.py:3154] 2023-12-09 13:05:33,270 >> ***** Running Prediction *****\n", "[INFO|trainer.py:3156] 2023-12-09 13:05:33,270 >> Num examples = 7988\n", "[INFO|trainer.py:3159] 2023-12-09 13:05:33,270 >> Batch size = 5\n", "100% 1598/1598 [00:38<00:00, 43.23it/s]12/09/2023 13:06:23 - INFO - utils_qa - Post-processing 7609 example predictions split into 7988 features.\n", "\n", " 0% 0/7609 [00:00> Dropping the following result as it does not have all the necessary fields:\n", "{'task': {'name': 'Question Answering', 'type': 'question-answering'}, 'dataset': {'name': 'squad_it', 'type': 'squad_it'}}\n", "100% 1598/1598 [01:14<00:00, 21.57it/s]\n" ] } ] }, { "cell_type": "code", "source": [], "metadata": { "id": "ij8YkY0xyNXI" }, "execution_count": null, "outputs": [] } ] }