End of training

.gitattributes

@@ -33,3 +33,5 @@ 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
+jax/jaxlib-0.4.26.dev20240504-cp310-cp310-manylinux2014_x86_64.whl filter=lfs diff=lfs merge=lfs -text
+v8-compile-cache-0/11.3.244.8-node.16/zSoptzScondazSsharezSjupyterzSlabzSstagingzSnode_moduleszSwebpackzSbinzSwebpack.js.BLOB filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,50 @@
+---
+license: mit
+base_model: gpt2
+tags:
+- trl
+- sft
+- generated_from_trainer
+model-index:
+- name: tmp
+  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. -->
+
+# tmp
+
+This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3.0
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.1.2
+- Datasets 2.19.2
+- Tokenizers 0.19.1

clean-layer.sh

@@ -0,0 +1,24 @@
+#!/bin/bash
+#
+# This scripts should be called at the end of each RUN command
+# in the Dockerfiles.
+#
+# Each RUN command creates a new layer that is stored separately.
+# At the end of each command, we should ensure we clean up downloaded
+# archives and source files used to produce binary to reduce the size
+# of the layer.
+set -e
+set -x
+
+# Delete files that pip caches when installing a package.
+rm -rf /root/.cache/pip/*
+# Delete old downloaded archive files 
+apt-get autoremove -y
+# Delete downloaded archive files
+apt-get clean
+# Ensures the current working directory won't be deleted
+cd /usr/local/src/
+# Delete source files used for building binaries
+rm -rf /usr/local/src/*
+# Delete conda downloaded tarballs
+conda clean -y --tarballs

config.json

@@ -0,0 +1,39 @@
+{
+  "_name_or_path": "gpt2",
+  "activation_function": "gelu_new",
+  "architectures": [
+    "GPT2LMHeadModel"
+  ],
+  "attn_pdrop": 0.1,
+  "bos_token_id": 50256,
+  "embd_pdrop": 0.1,
+  "eos_token_id": 50256,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_ctx": 1024,
+  "n_embd": 768,
+  "n_head": 12,
+  "n_inner": null,
+  "n_layer": 12,
+  "n_positions": 1024,
+  "reorder_and_upcast_attn": false,
+  "resid_pdrop": 0.1,
+  "scale_attn_by_inverse_layer_idx": false,
+  "scale_attn_weights": true,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "task_specific_params": {
+    "text-generation": {
+      "do_sample": true,
+      "max_length": 50
+    }
+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.2",
+  "use_cache": true,
+  "vocab_size": 50257
+}

core-js-banners

@@ -0,0 +1 @@
+["\u001b[96mThank you for using core-js (\u001b[94m https://github.com/zloirock/core-js \u001b[96m) for polyfilling JavaScript standard library!\u001b[0m\n\n\u001b[96mThe project needs your help! Please consider supporting of core-js:\u001b[0m\n\u001b[96m>\u001b[94m https://opencollective.com/core-js \u001b[0m\n\u001b[96m>\u001b[94m https://patreon.com/zloirock \u001b[0m\n\u001b[96m>\u001b[94m https://paypal.me/zloirock \u001b[0m\n\u001b[96m>\u001b[94m bitcoin: bc1qlea7544qtsmj2rayg0lthvza9fau63ux0fstcz \u001b[0m\n\n\u001b[96mAlso, the author of core-js (\u001b[94m https://github.com/zloirock \u001b[96m) is looking for a good job -)\u001b[0m\n","\u001b[96mThank you for using core-js (\u001b[94m https://github.com/zloirock/core-js \u001b[96m) for polyfilling JavaScript standard library!\u001b[0m\n\n\u001b[96mThe project needs your help! Please consider supporting of core-js:\u001b[0m\n\u001b[96m>\u001b[94m https://opencollective.com/core-js \u001b[0m\n\u001b[96m>\u001b[94m https://patreon.com/zloirock \u001b[0m\n\u001b[96m>\u001b[94m bitcoin: bc1qlea7544qtsmj2rayg0lthvza9fau63ux0fstcz \u001b[0m\n\n\u001b[96mAlso, the author of core-js (\u001b[94m https://github.com/zloirock \u001b[96m) is looking for a good job -)\u001b[0m\n"]

generation_config.json

@@ -0,0 +1,6 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 50256,
+  "eos_token_id": 50256,
+  "transformers_version": "4.41.2"
+}

jax/jaxlib-0.4.26.dev20240504-cp310-cp310-manylinux2014_x86_64.whl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:89855b059830f3e498c4fc71dde38fba040ae5ae6693efb88749a71b2c199b53
+size 132774266

keras_patch.sh

@@ -0,0 +1,41 @@
+#!/bin/bash
+
+# The following "sed" are to patch the current version of tf-df with
+# a fix for keras 3. In essence, replaces the use of package name "tf.keras" with 
+# "tf_keras"
+
+sed -i "/import tensorflow_decision_forests as tfdf/a import tf_keras" /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/__init__.py && \
+sed -i -e "/import tensorflow as tf/a import tf_keras" \
+       -e "/from yggdrasil_decision_forests.utils.distribute.implementations.grpc/a from tensorflow_decision_forests.keras import keras_internal" \
+       -e '/try:/{:a;N;/backend = tf.keras.backend/!ba;d}'\
+       /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/keras/core.py && \
+sed -i -e "s/from typing import Optional, List, Dict, Any, Union, NamedTuple/from typing import Any, Dict, List, NamedTuple, Optional, Union/g" \
+       -e "/import tensorflow as tf/a from tensorflow_decision_forests.keras import keras_internal" \
+       -e "/import tensorflow as tf/a import tf_keras" \
+       -e '/layers = tf.keras.layers/{:a;N;/backend = tf.keras.backend/!ba;d}' \
+       /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/keras/core_inference.py && \
+find /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests -type f -exec sed -i \
+     -e "s/get_data_handler/keras_internal.get_data_handler/g" \
+     -e 's/"models.Functional"/keras_internal.Functional/g' \
+     -e "s/tf.keras.utils.unpack_x_y_sample_weight/keras_internal.unpack_x_y_sample_weight/g" \
+     -e "s/tf.keras.utils.experimental/keras_internal/g" \
+     {} \; && \
+sed -i -e "/import tensorflow as tf/a import tf_keras" \
+       -e "/from tensorflow_decision_forests.keras import core/a from tensorflow_decision_forests.keras import keras_internal" \
+       -e '/layers = tf.keras.layers/{:a;N;/callbacks = tf.keras.callbacks/!ba;d}' \
+       /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/keras/keras_test.py && \
+find /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/keras -type f -exec sed -i \
+     -e "s/ layers.Input/ tf_keras.layers.Input/g" \
+     -e "s/layers.minimum/tf_keras.layers.minimum/g" \
+     -e "s/layers.Concatenate/tf_keras.layers.Concatenate/g" \
+     -e "s/layers.Dense/tf_keras.layers.Dense/g" \
+     -e "s/layers.experimental.preprocessing./tf_keras.layers./g" \
+     -e "s/layers.DenseFeatures/keras_internal.layers.DenseFeatures/g" \
+     -e "s/models.Model/tf_keras.models.Model/g" {} \; && \
+sed -i "s/ models.load_model/ tf_keras.models.load_model/g" /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/keras/keras_test.py && \
+sed -i "/import tensorflow as tf/a import tf_keras" /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/keras/test_runner.py && \
+sed -i "/import tensorflow as tf/a import tf_keras" /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/keras/wrappers.py && \
+sed -i -e "/import tensorflow as tf/a import tf_keras" \
+       -e "s/optimizer=optimizers.Adam()/optimizer=tf_keras.optimizers.Adam()/g" \
+       /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/keras/wrappers_pre_generated.py && \
+find /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests -type f -exec sed -i "s/tf.keras./tf_keras./g" {} \;

model.safetensors

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+oid sha256:c7d00560d8910fbed77ffad4065dee5011c41ba401b1064e749c498ba9e20373
+size 497774208

package_list

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+# This file may be used to create an environment using:
+# $ conda create --name <env> --file <this file>
+# platform: linux-64
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special_tokens_map.json

@@ -0,0 +1,6 @@
+{
+  "bos_token": "<|endoftext|>",
+  "eos_token": "<|endoftext|>",
+  "pad_token": "<|endoftext|>",
+  "unk_token": "<|endoftext|>"
+}

tmppptgk1qp/_remote_module_non_scriptable.py

@@ -0,0 +1,81 @@
+from typing import *
+
+import torch
+import torch.distributed.rpc as rpc
+from torch import Tensor
+from torch._jit_internal import Future
+from torch.distributed.rpc import RRef
+from typing import Tuple  # pyre-ignore: unused import
+
+
+module_interface_cls = None
+
+
+def forward_async(self, *args, **kwargs):
+    args = (self.module_rref, self.device, self.is_device_map_set, *args)
+    kwargs = {**kwargs}
+    return rpc.rpc_async(
+        self.module_rref.owner(),
+        _remote_forward,
+        args,
+        kwargs,
+    )
+
+
+def forward(self, *args, **kwargs):
+    args = (self.module_rref, self.device, self.is_device_map_set, *args)
+    kwargs = {**kwargs}
+    ret_fut = rpc.rpc_async(
+        self.module_rref.owner(),
+        _remote_forward,
+        args,
+        kwargs,
+    )
+    return ret_fut.wait()
+
+
+_generated_methods = [
+    forward_async,
+    forward,
+]
+
+
+
+
+def _remote_forward(
+    module_rref: RRef[module_interface_cls], device: str, is_device_map_set: bool, *args, **kwargs):
+    module = module_rref.local_value()
+    device = torch.device(device)
+
+    if device.type != "cuda":
+        return module.forward(*args, **kwargs)
+
+    # If the module is on a cuda device,
+    # move any CPU tensor in args or kwargs to the same cuda device.
+    # Since torch script does not support generator expression,
+    # have to use concatenation instead of
+    # ``tuple(i.to(device) if isinstance(i, Tensor) else i for i in *args)``.
+    args = (*args,)
+    out_args: Tuple[()] = ()
+    for arg in args:
+        arg = (arg.to(device),) if isinstance(arg, Tensor) else (arg,)
+        out_args = out_args + arg
+
+    kwargs = {**kwargs}
+    for k, v in kwargs.items():
+        if isinstance(v, Tensor):
+            kwargs[k] = kwargs[k].to(device)
+
+    if is_device_map_set:
+        return module.forward(*out_args, **kwargs)
+
+    # If the device map is empty, then only CPU tensors are allowed to send over wire,
+    # so have to move any GPU tensor to CPU in the output.
+    # Since torch script does not support generator expression,
+    # have to use concatenation instead of
+    # ``tuple(i.cpu() if isinstance(i, Tensor) else i for i in module.forward(*out_args, **kwargs))``.
+    ret: Tuple[()] = ()
+    for i in module.forward(*out_args, **kwargs):
+        i = (i.cpu(),) if isinstance(i, Tensor) else (i,)
+        ret = ret + i
+    return ret

tokenizer_config.json

@@ -0,0 +1,20 @@
+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "50256": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<|endoftext|>",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|endoftext|>",
+  "model_max_length": 1024,
+  "pad_token": "<|endoftext|>",
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": "<|endoftext|>"
+}

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c4585d6ab52a9193968e9b7134131d165132edc4036d5c4adbfaa70a0ba3dbb5
+size 5304

v8-compile-cache-0/11.3.244.8-node.16/zSoptzScondazSsharezSjupyterzSlabzSstagingzSnode_moduleszSwebpackzSbinzSwebpack.js.BLOB

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+version https://git-lfs.github.com/spec/v1
+oid sha256:0e1d585bb02b985ec668a78261aed811e24963f00ac15bf945a945de1f32f956
+size 4604272

yarn--1704964927164-0.1782869183766309/node

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "$@"

yarn--1704964927165-0.35993847591915795/node

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "$@"

yarn--1704964927165-0.35993847591915795/yarn

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "/opt/conda/share/jupyter/lab/staging/yarn.js" "$@"

yarn--1704964928127-0.35887085411210307/node

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "$@"

yarn--1704964928127-0.35887085411210307/yarn

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "/opt/conda/share/jupyter/lab/staging/yarn.js" "$@"

yarn--1704964933548-0.9586437363349738/node

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "$@"

yarn--1704964933548-0.9586437363349738/yarn

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "/opt/conda/share/jupyter/lab/staging/yarn.js" "$@"

yarn--1704965062369-0.2181574829625219/node

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "$@"

yarn--1704965062369-0.2181574829625219/yarn

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "/opt/conda/share/jupyter/lab/staging/yarn.js" "$@"

yarn--1704965063359-0.7469983285256505/node

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "$@"

yarn--1704965063359-0.7469983285256505/yarn

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "/opt/conda/share/jupyter/lab/staging/yarn.js" "$@"

yarn--1704965068891-0.46018400452963615/node

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "$@"

yarn--1704965068891-0.46018400452963615/yarn

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "/opt/conda/share/jupyter/lab/staging/yarn.js" "$@"